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Drone-Mounted Ultrawideband Radar for Retrieval of Snowpack Properties
Abstract
Extracting snowpack parameters from snow cover on sea ice or land is a time-consuming and potentially high-risk task. Moreover, deriving such parameters by manually digging a snow pit evidently yields low area coverage. We, therefore, propose a practical solution to this problem by mounting an ultrawideband radar system onto an UAV to obtain information such as snowpack depth, density, and stratigraphy in order to increase personnel safety and extend coverage area. In this paper, we describe the development of radar system hardware and its mounting onto a UAV, as well as initial tests with this radar as a snow measuring device. Preliminary results from both ground and airborne testing show that the radar system is capable of obtaining snow depth information that corresponds well to in situ validation data with a correlation of 0.87. The radar system also works well while mounted on a UAV platform with little additional signal noise from vibrational and translatory movements.
... For this reason, the ground-penetrating radar (GPR) [2] is gaining increasing attention as a complementary remote sensing instrument onboard UAV platforms, and the scientific community, as well as various industries, is attempting to develop innovative and effective UAV-based GPR systems . The combination of UAV and GPR technology can lead to the creation of innovative imaging systems, which could be exploited in many applicative contexts, such as landmine detection [3,[5][6][7]9,10,15,17], glaciology [8,19,23], search and rescue [8], agriculture [16], environmental monitoring [4,11,18], and cultural heritage [12]. ...
... For this reason, the ground-penetrating radar (GPR) [2] is gaining increasing attention as a complementary remote sensing instrument onboard UAV platforms, and the scientific community, as well as various industries, is attempting to develop innovative and effective UAV-based GPR systems . The combination of UAV and GPR technology can lead to the creation of innovative imaging systems, which could be exploited in many applicative contexts, such as landmine detection [3,[5][6][7]9,10,15,17], glaciology [8,19,23], search and rescue [8], agriculture [16], environmental monitoring [4,11,18], and cultural heritage [12]. ...
... System 5 is an ultra-wide-band snow sounder (UWiBaSS) GPR developed by Norut Northern Research Institute (Norway) in 2018 for snowpack surveying [8]. The radar module is the M-Sequence UWB sensor developed by the German company ILMSENS (https://www.uwb-shop.com/, ...
Radar imaging from unmanned aerial vehicles (UAVs) is a dynamic research topic attracting huge interest due to its practical fallouts. In this context, this article provides a comprehensive review of the current state of the art and challenges related to UAV-based ground-penetrating radar (GPR) imaging systems. First, a description of the available prototypes is provided in terms of radar technology, UAV platforms, and navigation control devices. Afterward, the paper addresses the main issues affecting the performance of UAV-based GPR imaging systems. such as the control of the UAV platform during the flight to collect high-quality data, the necessity to provide accurate platform position information in terms of probing wavelength, and the mitigation of clutter and other electromagnetic disturbances. A description of the major applicative areas for UAV GPR systems is reported with the aim to show their potential. Furthermore, the main signal-processing approaches currently adopted are detailed and two experimental tests are also reported to prove the actual imaging capabilities. Finally, open challenges and future perspectives regarding this promising technology are discussed.
... UAS-borne radars could cover larger areas with respect to terrestrial systems, with a shorter return time. These two characteristics, combined with the flexibility of UAS systems, allow for the use of UAS in different applications, such as landmine detection [12], snow/ice monitoring [13], deformation measurement [14], and biomass survey [15]. Compared to conventional systems, the UAS radar can be deployed within minutes and used in scenarios where ground systems cannot be operated. ...
... For UAS applications, the FMCW is the most used (63% of papers), followed by pulsed equipment (18%), and finally SFCW (2.5%). In [13,26,27], Jessen et al. used a pseudo noise transceiver, which is an advanced modulation technique usually used for military purposes since it is more robust against the interference (it cannot be easily intercepted or jammed). Moreover, the authors selected this modulation due to a flatter amplitude inside the transmitted bandwidth, and a higher duty cycle. ...
... applications, the FMCW is the most used (63% of papers), followed by pulsed equipment (18%), and finally SFCW (2.5%). In [13,26,27], Jessen et al. used a pseudo noise transceiver, which is an advanced modulation technique usually used for military purposes since it is more robust against the interference (it cannot be easily intercepted or jammed). Moreover, the authors selected this modulation due to a flatter amplitude inside the transmitted bandwidth, and a higher duty cycle. ...
Since the 1950s, radar sensors have been widely used for the monitoring of the earth’s surface. The current radars for remote sensing can be divided into two main categories: Space/aerial-borne and ground-based systems. The unmanned aerial system (UAS) could bridge the gap between these two technologies. Indeed, UAS-borne radars can perform long scans (up to 100/200 m) in a brief time (a few minutes). From the 2010s, the interest in UAS-borne radars has increased in the research community, and it has led to the development of some commercial equipment and more than 150 papers. This review aims to present a study on the state-of-the-art of UAS-borne radars and to outline the future potential of this technology. In this work, the scientific literature was categorized in terms of application, purpose of the paper, radar technology, and type of UAS. In addition, a brief review of the main national UAS regulations is presented. The review on the technological state-of-the-art shows that there is currently no standard in terms of radar technology, and that the multi-helicopter could be the most used UAS in the near future. Moreover, the UAS-borne radar can be used for several remote sensing applications: From landmine detection to smart agriculture, and from archeological survey to research and rescue applications. Finally, the UAS-borne radar appears to be a mature technology, which is almost ready for industrialization. The main developmental limit may be found in the flight regulation, which does not allow for many operations and imposes strict limits on the payload weight.
... Các UAV có thể cất, hạ cánh từ các khu vực nhỏ và có thể di chuyển theo mọi hướng và trên các địa hình phức tạp. Lợi dụng các ưu điểm này, cộng đồng khoa học đã phát triển các hệ thống GPR đặt trên UAV (viết tắt là GPR-UAV) để khắc phục nhược điểm của GPR truyền thống, từ đó mở rộng phạm vi hoạt động của GPR [1], tạo ra các hệ thống ứng dụng trong nhiều bối cảnh, như phát hiện bom mìn [2], [3], tìm kiếm cứu nạn [4], nông nghiệp [5], giám sát môi trường [6], [7], [8], v.v. ...
... Một GPR nhẹ làm việc tại băng thông 56 MHz, được điều chế bởi tín hiệu sóng mang ở 2 GHz dưới dạng bộ lọc cosine nâng (RCF), hai ăng-ten Vivaldi Antipodal được lắp đặt ở cấu hình bistatic với góc nghiêng 45° được công bố vào năm 2017 [1]. Vào năm 2018, Viện Nghiên cứu Bắc Norut (Na Uy) phát triển một GPR để phát hiện tuyết [4]. Một hệ thống GPR nhỏ gọn với băng thông siêu rộng (hoạt động trong dải tần số từ 1-4 GHz) để phát hiện mìn cũng được công bố [2] [3]. ...
Radar xuyên đất (Ground-Penetrating Radar, GPR) lợi dụng khả năng có thể xuyên qua các vật liệu không nhìn thấy bằng mắt thường để phát hiện và tạo dựng hình ảnh các vật thể bị chôn vùi, ẩn giấu dưới lòng đất đã và đang được sử dụng rộng rãi như một công cụ cảm biến từ xa. Đối với địa hình phức tạp, radar xuyên đất khó triển khai theo phương pháp truyền thống, như đặt trên xe đẩy. Với sự phát triển của nền tảng máy bay không người lái (Unmanned Aerial Vehicles, UAV), các hệ thống GPR gắn trên UAV giúp mở rộng khả năng làm việc và tăng hiệu quả của GPR. Trong bài báo này, đầu tiên chúng tôi giới thiệu tổng quan các nghiên cứu về hệ thống radar xuyên đất gắn trên UAV. Tiếp theo, dựa trên kết quả phân tích tổng quan, lý thuyết tính toán và yêu cầu thực tiễn, một hệ thống radar xuyên đất gắn trên UAV do chúng tôi thiết kế, chế tạo và thực nghiệm được trình bày chi tiết. Cuối cùng, chúng tôi đánh giá những yếu tố ảnh hưởng đến chất lượng và các triển vọng tương lai liên quan đến công nghệ này.
... Over the past decade, UAV-based radar imaging has seen significant advancement, with various radar technologies, unmanned platforms, and payload configurations showcased [390][391][392][393][394][395]. Early research by [396,397] laid the foundation, leading to tests with high-frequency radars at P, X, and C bands [398][399][400], despite limited penetration capabilities. ...
... UAV-borne GPR systems rely on antennas to convert guided waves [424,448]. Modern UAV-compatible antennas include Vivaldi-like antennas, Archimedean spiral antennas, and helix antennas, as reported in [24,393,413,414,422], detailed in Table 18. Antennas in UAV-based GPR systems prioritize weight, dimensions, and radiation performance, often favoring horn-like or planar designs. ...
Geophysical surveys, a conventional means of analyzing the Earth and its environs, have traditionally relied on ground-based methodologies. However, up-to-date approaches encompass remote sensing (RS) techniques, employing both spaceborne and airborne platforms. The emergence of Unmanned Aerial Vehicles (UAVs) has notably catalyzed interest in UAV-borne geophysical RS. This study comprehensively reviews the state-of-the-art UAV-based geophysical methods, encompassing magnetometry, gravimetry, gamma-ray spectrometry/radiometry, electromagnetic (EM) surveys, ground penetrating radar (GPR), traditional UAV RS methods (i.e., photogrammetry and LiDARgrammetry), and integrated approaches. Each method is scrutinized concerning essential aspects such as sensors, platforms, challenges, applications, etc. Drawing upon an extensive review of over 435 scholarly works, our analysis reveals the versatility of these systems, ranging from geophysical development to applications over various geoscientific domains. The reviewed studies unanimously highlight the advantages of UAV RS in geophysical surveys. UAV geophysical RS effectively balances the benefits of ground-based and traditional RS methods regarding cost, resolution, accuracy, and other factors. Integrating multiple sensors on a single platform and fusion of multi-source data enhance efficiency in geoscientific analysis. However, implementing geophysical methods on UAVs poses challenges, prompting ongoing research and development efforts worldwide to find optimal solutions from both hardware and software perspectives.
... Due to low operating cost and noninvasive field data collection capability, an unmanned aerial vehicle (UAV)mounted ultrawideband (UWB) ground penetrating radar (GPR) received much attention in various applications such as buried mines detection, 1 soil moisture mapping, 2 snow thickness measurement, 3,4 and mapping of civil infrastructure. 5 To analyze the internal layers of the ground (soil, ice, or snow) with fine resolution, the GPR requires an UWB system. ...
... where c is the speed of light and ε r is the complex permittivity of the medium. 3 Further, the GPR demands a system with a low first crossing frequency (f L ) of the voltage standing wave ratio (VSWR) under 2 and high antenna gain because the attenuation of electromagnetic (EM) waves increases with frequency as it penetrates the medium. f L of 500 MHz is needed to penetrate 4 m thick of 5% wet snow ground. ...
This paper presents a novel high‐gain, miniaturized, and ultra‐wideband tapered‐slot Vivaldi antenna (TSVA) for ice‐sounding radar applications. To miniaturize the antenna and improve the impedance matching and antenna gain of conventional TSVA, tapered slot edge, circular cavity, rectangular cavity, inner circular patch, and rectangular slit structures are newly designed and introduced. The simulation results show that the size of the designed Vivaldi antenna is reduced by 15% and increases the peak realized gain by up to 5.1 dBi, compared to the conventional Vivaldi antenna. The optimized Vivaldi antenna was fabricated and characterized for its antenna performance. The simulated results are in good agreement with the measured results.
... In [27], [28], the trajectory and precoder of UAV-BS are optimized to maximize physical layer secrecy. In [29], a UAV-radar is used in measuring the depth of the snow on the sea. Human detection and classification by a UAV-radar have been studied in [30]. ...
... The maximum node densities λ d and λ s.o. r can be obtained when (29) goes to equality. Note that this analysis can be easily extended to the condition that λ d and λ s.o. ...
Unmanned aerial vehicles (UAVs) are expected to be used extensively in the future for various applications, either as user equipment (UEs) connected to a cellular wireless network, or as an infrastructure extension of an existing wireless network to serve other UEs. Next generation wireless networks will consider the use of UAVs for joint communication and radar and/or as dedicated radars for various sensing applications. Increasing number of UAVs will naturally result in larger number of communication and/or radar links that may cause interference to nearby networks, exacerbated further by the higher likelihood of line-of-sight signal propagation from UAVs even to distant receivers. With all these, it is critical to study network coexistence of UAV-mounted base stations (BSs) and radar transceivers. In this paper, using stochastic geometry, we derive closed-form expressions to characterize the performance of coexisting UAV radar and communication networks for spectrum overlay multiple access (SOMA) and time-division multiple access (TDMA). We evaluate successful ranging probability (SRP) and the transmission capacity (TC) and compare the performance of TDMA and SOMA. Our results show that SOMA can outperform TDMA on both SRP and TC when the node density of active UAV-radars is larger than the node density of UAV-comms.
... The drones, compared to the helicopter, can enjoy a much lower flight altitude, down to about 1 m according to our experience. The application of drone-borne GPR to investigate glacier environments is a novelty in the literature and has only been addressed by a few studies, such as Jenssen et al. (2018Jenssen et al. ( , 2020 [19,20]. Those works focus on the development of an ultrawideband radar antenna, operating in a frequency band between 0.95 to 6 GHz, which can be mounted effectively on an octocopter drone. ...
... A better vertical resolving power could be achieved by adopting higher frequency antennas: a customized release of the commercial antennas up to 2 GHz could be easily implemented in our system, allowing us to double the vertical resolution. Recent research tested a specifically built antenna for airborne GPR surveys, designing a specific unambiguous range, range resolution, and frequency bandwidth [20]. Their results on the snow cover test point out that airborne surveys can reach good accuracy and resolution with an adequate design. ...
Ground-penetrating radar (GPR) is one of the most commonly used instruments to map the Snow Water Equivalent (SWE) in mountainous regions. However, some areas may be difficult or dangerous to access; besides, some surveys can be quite time-consuming. We test a new system to fulfill the need to speed up the acquisition process for the analysis of the SWE and to access remote or dangerous areas. A GPR antenna (900 MHz) is mounted on a drone prototype designed to carry heavy instruments, fly safely at high altitudes, and avoid interference of the GPR signal. A survey of two test sites of the Alpine region during winter 2020–2021 is presented, to check the prototype performance for mapping the snow thickness at the catchment scale. We process the data according to a standard flow-chart of radar processing and we pick both the travel times of the air–snow interface and the snow–ground interface to compute the travel time difference and to estimate the snow depth. The calibration of the radar snow depth is performed by comparing the radar travel times with snow depth measurements at preselected stations. The main results show fairly good reliability and performance in terms of data quality, accuracy, and spatial resolution in snow depth monitoring. We tested the device in the condition of low snow density (
... Operating in the 1-300 GHz range, these sensors can penetrate vegetation canopies to provide insights into underlying soil conditions. The authors of [36] demonstrated the effectiveness of drone-mounted ultrawideband radar for retrieving snowpack properties, which is crucial for predicting spring soil moisture conditions in snow-affected agricultural regions. This non-invasive technique accurately measures snow depth and density, aiding in water resource management for agriculture. ...
In the face of growing challenges in modern agriculture, such as climate change, sustainable resource management, and food security, drones are emerging as essential tools for transforming precision agriculture. This systematic review, based on an in-depth analysis of recent scientific literature (2020–2024), provides a comprehensive synthesis of current drone applications in the agricultural sector, primarily focusing on studies from this period while including a few notable exceptions of particular interest. Our study examines in detail the technological advancements in drone systems, including innovative aerial platforms, cutting-edge multispectral and hyperspectral sensors, and advanced navigation and communication systems. We analyze diagnostic applications, such as crop monitoring and multispectral mapping, as well as interventional applications like precision spraying and drone-assisted seeding. The integration of artificial intelligence and IoTs in analyzing drone-collected data is highlighted, demonstrating significant improvements in early disease detection, yield estimation, and irrigation management. Specific case studies illustrate the effectiveness of drones in various crops, from viticulture to cereal cultivation. Despite these advancements, we identify several obstacles to widespread drone adoption, including regulatory, technological, and socio-economic challenges. This study particularly emphasizes the need to harmonize regulations on beyond visual line of sight (BVLOS) flights and improve economic accessibility for small-scale farmers. This review also identifies key opportunities for future research, including the use of drone swarms, improved energy autonomy, and the development of more sophisticated decision-support systems integrating drone data. In conclusion, we underscore the transformative potential of drones as a key technology for more sustainable, productive, and resilient agriculture in the face of global challenges in the 21st century, while highlighting the need for an integrated approach combining technological innovation, adapted policies, and farmer training.
... Remote sensing methods use GPR to measure the snow layers under the snow cover by processing the reflections from the radar without making contact with the snow. GPR have recently gained interest as it can rapidly provide dense snow depth measurements over a large area (Jenssen et al., 2019;Berg-Jensen, 2021;Vergnano et al., 2022;Teisberg et al., 2022). However, GPR measurements lack the required depth resolution, as the theoretical lower bound of the measurement resolution is larger than the necessary resolution to detect weak layers (McCammon and Schweizer, 2002;Frauenfelder et al., 2022). ...
Snow stratigraphy measurements provide important information for determining snowpack stability. However, acquiring these measurements, especially on high-aspect slopes, remains a high-risk task due to the exposure of the operator to the intrinsic avalanche hazard. Therefore, to date, little to no snow stratigraphy measurements have ever been acquired on high-risk slopes. In this work, we propose a novel solution that combines an autonomous aerial robotic system that can deploy an SMP-like measurement device into steep slopes. We achieve this by using an adaptive landing leg that allows reliable autonomous landing and taking off from steep slopes of up to 45 degrees. The vehicle uses a digital elevation map to automatically orient the vehicle's heading and landing gear. We evaluated our system on a deployment over two snow-covered slopes located in Davos, Switzerland. We demonstrated that the vehicle can successfully take snow stratigraphy measurements by landing on arbitrary locations on the terrain up to 38 degrees.
... Operational guidelines are provided by Dupuy et al. (2023). Processing of the GPR data is done using a custom workflow based on Python and RGPR (Huber and Hans, 2018) open-source libraries. It consists of several sequential steps aiming at improving signal to noise ratio for better visualisation while conserving arrival times, phases and amplitudes for further quantitative investigations. ...
... Snow thickness measurements using airborne microwave radars have been successfully demonstrated by several groups around the world [1][2][3]. Our group at the University of Kansas developed various nadir-looking ultra-wideband (UWB) frequency-modulated continuous wave (FMCW) microwave radars for measuring snow pile up. ...
... Identifying areas at risk and monitoring the occurrence and spread of flood [43,[52][53][54][55][56] Identifying areas at risk and monitoring the occurrence and spread of fire [51][52][53] Monitoring the generation of destructive primary lahars responsible for the volcanic eruption [ Monitoring the driving and dangerous behaviour of cyclists [90] Water environment Sampling and testing of waters [93][94][95][96] Studying the behaviour of sea creatures [97] Ocean observation to model tropical cyclones [98] Monitoring for shark warnings [99] Mapping the distribution of vegetation that provides habitat for sea creatures [100] Monitoring reefs and factors affecting seaweed growth [101] Monitoring critical phenomena to support the management of aquaculture farms [102] Spatial modelling of salt marshes [103] Infrastructure Three-dimensional mapping of selected infrastructure facilities [106] Condition monitoring of transmission networks [104,105] Assessment of the thermal quality of buildings [107] Identification of traces of historical objects [108] Emission of pollution Emission of selected chemical compounds during forest burning [109] Monitoring of air pollution in a selected area [115,116] Measurement of radiological contamination, monitoring of radiation distribution [110,111] Identification of areas where diffuse pollution from agriculture occurs [112] Dispersion of volatile chemicals [113] Mapping of soil contamination [114] Landslides Survey of open pit mine slopes [122] Creating landslide maps for risk assessment [117][118][119][120][121] Monitoring of landslides of rubble and rocks [123,124] Detecting cracks in retaining walls [125] Inspection Conducting inspections of unburied land pipelines [127] Identifying corrosion in industrial structures such as telecommunications towers and wind farms [129,130] Conducting inspections of safety-critical infrastructure [131] Tracking construction progress [132,133] Inspecting terrain for unexploded ordnance and landmines [134,135] Inspecting bridge and road infrastructure [38,136] Other Detection of asbestos roof slates [137] Investigation of orphaned wells [138] Snowpack depth, density, and stratigraphy study [139] Land management [140] Improvement of terrestrial wireless cellular networks [141] Fracture distribution and orientation in outcrops [142] The analysis of the above publications made it possible to conclude that in the process of monitoring, the use of drones serves as a supplement to the measurement for the field surveys carried out (the field surveys are carried out first and then supplemented with data from the drone) or as a system reporting the need for additional research (identifying a specific phenomenon that requires additional research). The authors of the publication point out in their research the benefits of drone use, such as: ...
This article aims to present the results of a bibliometric analysis of relevant literature and discuss the main research streams related to the topic of risks in drone applications. The methodology of the conducted research consisted of five procedural steps, including the planning of the research, conducting a systematic review of the literature, proposing a classification framework corresponding to contemporary research trends related to the risk of drone applications, and compiling the characteristics of the publications assigned to each of the highlighted thematic groups. This systematic literature review used the PRISMA method. A total of 257 documents comprising articles and conference proceedings were analysed. On this basis, eight thematic categories related to the use of drones and the risks associated with their operation were distinguished. Due to the high content within two of these categories, a further division into subcategories was proposed to illustrate the research topics better. The conducted investigation made it possible to identify the current research trends related to the risk of drone use and pointed out the existing research gaps, both in the area of risk assessment methodology and in its application areas. The results obtained from the analysis can provide interesting material for both industry and academia.
... Such structure [42,43] can provide wide BW behaviour, and depending upon the requirement, careful design, and substrate specification, UWB behaviour can be obtained. A typical wideband antenna utilizes the operating spectrum efficiently in radar systems with a high spatial resolution for defense systems [44], mobile phones, and many handy devices [45,46]. In addition, it can be used in numerous types of biomedical applications, including heartbeat monitoring [47]. ...
This paper proposes a novel scheme for developing a linearly polarized (LP) hybrid antenna using a simple integration of a planner cavity-backed antenna with a conventional rectangular patch antenna. To substantiate, a half-mode rectangular substrate-integrated waveguide technique is divided into halves to reduce the size and later integrated with a patch antenna. The patch antenna is getting excited by the mutual coupling of TE101 mode and resonating in the vicinity of the cavity resonator. These two different combinations of strategy let the antenna obtain superior characteristics such as bandwidth and gain. To make this structure enable to use in the planner circuit, a 50 Ω microstrip line is incorporated. This proposed hybrid antenna is simulated and tested experimentally to justify its worthiness. The simulated and measured data maintained good agreements regarding S 11 , bandwidth, gain, radiation pattern, and efficiency.
... Improved ultra-wideband radars (UWBs) have also been installed in airplanes to find out the snow depth on the Arctic sea ice [9]. In addition, recently unmanned aerial vehicles (UAVs), known as drones, have been used to retrieve snow depth information on sea ice [10]. One solution is to use satellite microwave remote sensing data for the snow depth estimation on lake and sea ice [11,12]. ...
In this work, backscattering signatures of snow-covered lake ice and sea ice from X- and Ku-band synthetic aperture radar (SAR) data are investigated. The SAR data were acquired with the ESA airborne SnowSAR sensor in winter 2012 over Lake Orajärvi in northern Finland and over landfast ice in the Bay of Bothnia of the Baltic Sea. Co-incident with the SnowSAR acquisitions, in situ snow and ice data were measured. In addition, time series of TerraSAR-X images and ice mass balance buoy data were acquired for Lake Orajärvi in 2011–2012. The main objective of our study was to investigate relationships between SAR backscattering signatures and snow depth over lake and sea ice, with the ultimate objective of assessing the feasibility of retrieval of snow characteristics using X- and Ku-band dual-polarization (VV and VH) SAR over freshwater or sea ice. This study constitutes the first comprehensive survey of snow backscattering signatures at these two combined frequencies over both lake and sea ice. For lake ice, we show that X-band VH-polarized backscattering coefficient (σo) and the Ku-band VV/VH-ratio exhibited the highest sensitivity to the snow depth. For sea ice, the highest sensitivity to the snow depth was found from the Ku-band VV-polarized σo and the Ku-band VV/VH-ratio. However, the observed relations were relatively weak, indicating that at least for the prevailing snow conditions, obtaining reliable estimates of snow depth over lake and sea ice would be challenging using only X- and Ku-band backscattering information.
... As a result, these systems are particularly useful for detecting landmines and Improvised Explosive Devices (IEDs) as they allow a fast inspection of the subsurface while keeping a safety distance to avoid accidental detonations [3]- [7]. Furthermore, they have been also successfully used for other applications, such as measurements of soil moisture [8] or snowpack thickness [9]. ...
Ground Penetrating Radar (GPR) systems on board Unmanned Aerial Vehicles (UAVs) have been successfully used for subsurface imaging applications. Their capability to detect buried targets avoiding the contact with the soil turn these systems into a great solution to detect buried threats, such as landmines and Improvised Explosive Devices (IEDs). Significant advances have been also conducted to enhance the detection capabilities of these systems, complementing the Synthetic Aperture Radar (SAR) processing methods with several clutter mitigation techniques. However, the improvement in the scanning throughput (i.e., increasing the inspected area in a given time) remains a significant challenge. In this regard, this article compares several scanning strategies for UAV-mounted multichannel GPR-SAR systems using antenna arrays. In particular, two different scanning strategies have been compared: a uniform scheme and a non-uniform strategy called 3X. In addition, different across-track spacing values to generate dense and sparse sampling distributions were considered for each scanning scheme. After conducting a theoretical analysis of these strategies, they have been experimentally validated with measurements gathered with a portable scanner and during flights in realistic scenarios. Results show that the dense configurations of both scanning strategies yield good quality images of buried targets while improving the scanning throughput (compared to a single-channel architecture). In particular, the dense uniform scheme (with a 20 cm across-track spacing) achieves a greater reduction in the inspection time, compared to the dense 3X strategy, at the expense of a slightly smaller signal to clutter ratio.
... Another key application of UAS-based GPR systems is the study and monitoring of snow cover parameters. Also in this case, ultrawideband radar systems have demonstrated to achieve high performances, and some prototypes have been developed and tested in different case studies [10]- [12]. Besides, other works explore the possibility of using UAS-GPR systems to perform measurements of soil moisture [13], achieving good results. ...
... Parallelly, the technological progress has led the development of GPR systems that can be used remotely with an extremely high signal-to-noise ratio. Some examples of this upgraded configuration are mainly related to landmine detection (Garcia-Fernandez et al. 2018a;Garcia-Fernandez et al. 2019a, 2019bGarcia-Fernandez et al. 2022;Šipoš and Gleich 2020), snowpack and glaciology research (McCallum and Fairweather 2013;Tan et al. 2017;Briggs et al. 2018;Eckerstorfer et al. 2018;Jenssen et al. 2020;Prager et al. 2022;Vergnano et al. 2022;Emilsson et al. 2022), agricultural research (Wu et al. 2019;Hou et al. 2021), archaeological survey (Yarleque et al. 2017;Colica et al. 2022), soil characteristics under railways mapping (Bayisa et al. 2015), investigation of water and sediment depths of lakes and rivers (Bandini et al. 2022), and buried objects detection (Ludeno et al. 2017). ...
This paper describes scientific research conducted to highlight the potential of an integrated GPR-UAV system in engineering-geological applications. The analysis focused on the stability of a natural scree slope in the Germanasca Valley, in the western Italian Alps. As a consequence of its steep shape and the related geological hazard, the study used different remote sensed methodologies such as UAV photogrammetry and geophysics survey by a GPR-drone integrated system. Furthermore, conventional in-situ surveys led to the collection of geological and geomorphological data. The use of the UAV-mounted GPR allowed us to investigate the bedrock depth under the detrital slope deposit, using a non-invasive technique able to conduct surveys on inaccessible areas prone to hazardous conditions for operators. The collected evidence and the results of the analysis highlighted the stability of the slope with Factors of Safety, verified in static conditions (i.e., natural static condition and static condition with snow cover), slightly above the stability limit value of 1. On the contrary, the dynamic loading conditions (i.e., seismic action applied) showed a Factor of Safety below the stability limit value. The UAV-mounted GPR represented an essential contribution to the surveys allowing the definition of the interface debris deposit-bedrock, which are useful to design the slope model and to evaluate the scree slope stability in different conditions.
... Improved ultra wideband radars (UWBs) have also been installed in airplanes to find 2 out the snow depth on the Arctic sea ice [9]. In addition, recently unmanned aerial vehicles (UAVs), known as drones, have been used to retrieve snow depth information on sea ice [10]. One solution is to use satellite microwave remote sensing data for the snow depth estimation on lake and sea ice [11,12]. ...
In this work, backscattering signatures of snow-covered lake ice and sea ice from X- and Ku-band synthetic aperture radar (SAR) data are investigated. The SAR data were acquired with the ESA airborne SnowSAR sensor in winter 2012 over Lake Orajärvi in northern Finland and over landfast ice in the Bay of Bothnia of the Baltic Sea. Co-incident with the SnowSAR acquisitions in-situ snow and ice data were measured. In addition, time series of TerraSAR-X images and ice mass balance buoy data were acquired for the Lake Orajärvi in 2011-12. The main objective of our study was to investigate relationships between SAR backscattering signatures and snow depth over lake and sea ice, with the ultimate objective of assessing the feasibility of retrieval of snow characteristics using X- and Ku-band dual-polarisation (VV and VH) SAR over freshwater or sea ice. This study constitutes the first comprehensive survey of snow backscattering signatures at these two combined frequencies over both lake and sea ice. For lake ice, we show that X-band VH-polarized backscattering coefficient (σo) and the Ku-band VV/VH-ratio exhibited the highest sensitivity to the snow depth. For sea ice, the highest sensitivity to the snow depth was found from the Ku-band VV-polarised σo and the Ku-band VV/VH-ratio. However, the observed relations were relatively weak, indicating that at least for the prevailing snow conditions, obtaining reliable estimates of snow depth over lake and sea ice would be challenging using only X- and Ku-band backscattering information.
... Other UAS-based remote sensors that are being tested include multispectral cameras (Maier et al., 2022) and thermal cameras (Steinkogler et al., 2015). Subsurface mapping using ground penetrating radar (GPR) mounted on drones has been given less attention so far, and outcomes can be ambiguous (Jenssen et al., 2019, Valence et al., 2022. ...
... Reviews of the state-of-the-art of UAV-based GPR systems have been presented in [14], [15], [16], describing the main features and challenges faced by these systems. Although most of the UAV-based GPR system prototypes developed in the last years have been devoted to detecting landmines and IEDs, they have been also introduced in other application areas like snow moisture and ice thickness measurement [17], [18], soil moisture characterization [19], or search and rescue missions [20], [21], among others. ...
The usage of Unmanned Aerial Vehicles (UAV)-based Ground Penetrating Radar (GPR) systems has gained interest over the last years thanks to advantages over ground-based systems such as contactless inspection and capability to reach difficult-to-access areas. The former is of paramount importance concerning the detection of buried threats such as Improvised Explosive Devices (IEDs) and landmines. Current state-of-the-art UAV-based GPR systems are able to provide centimeter-level resolution thanks to the use of GPR-Synthetic Aperture Radar (SAR) processing techniques. One of the challenges to keep improving these systems is the scanning throughput, that is, the area that can be scanned in a given time. This contribution presents an array-based GPR-SAR system for subsurface imaging, aiming at maximizing the scanning throughput without jeopardizing the imaging capabilities of the system. First, the antenna array is mounted on a portable setup to evaluate its performance and imaging capabilities. Next, the antenna array is integrated into the UAV platform, and the UAV-based GPR-SAR system with the array is tested in realistic scenarios with different kinds of buried targets. Results show that the scanning throughput is significantly improved and, furthermore, the coherent combination of all transmitting-receiving channels of the array provides enhanced detection capabilities.
... Also, the sUAS radar must be operated at as high altitudes as possible in conformance with Federal Aviation Administration (FAA) regulations to collect data over areas covered with heavy vegetation over complex terrain. Tan et al. [14] and Jessen et al. [15]- [17] designed and tested UWB UASbased radars using a vector network analyzer or a Pseudo noise signal generator for snow depth measurements. However, the short unambiguous range of these systems limits their benefits to open areas. ...
This paper presents results from a field deployment of a small Unmanned Aircraft System (sUAS) radar in Colorado-Grand Mesa during Spring-2022 for measurements over snow. The stand-alone, low-power, compact, and Frequency Modulated Continuous Wave (FMCW) radar on a sUAS is used for these measurements. The radar operates over the frequency range of 2.8-5.8 GHz. The transmit signal is obtained by down-converting 77-81 GHz chirp generated with an automotive radar. The radar operates with a low output power of only 3 dBm (2 mW) to mitigate interference to nearby communication systems with a chirp duration of 250 μs. The received signal is up-converted back to 77-81 GHz for digitization and processing using the automotive radar data capture board. The radar data are processed with a fully focused Synthetic Aperture Radar (SAR) algorithm after applying phase and amplitude corrections to the transmitter chirp to obtain nearly ideal point target responses. The radar mapped air-snow and snow-ground surface interfaces as well as the snow internal layers with snow depth exceeding 2 m in areas covered with 15-25 m tall trees. In addition, the radar-generated snow thicknesses are within ±10 cm of in-situ measurements.
... However, even though the satellite platforms can cover large areas, the resolution is coarse for measurements over complex terrains. On the other hand, Tan et al. and Jessan et al. demonstrated the snow measurements using low-cost drone platforms with fine resolution [24][25][26]. Airborne platforms like DHC-6 Twin Otter give a unique advantage in bridging this gap and can cover broad areas with very fine resolution. A combination of manned aircraft with drones can provide both fine-resolution data over small areas and modest resolution data over large areas. ...
We developed and deployed a high sensitivity and low transmit power airborne UWB FMCW radar for snow depth measurements. The radar has a near-ideal point target response so that we can produce near-real-time snow thickness maps after each survey flight. The improved performance is achieved by carefully designing the radar hardware to reduce internal reflections between various components, third-order products generated by mixers, higher-order harmonics generated in multipliers and non-linear devices, and amplitude and phase errors in transmitted chirp signals. In addition, we performed extensive linear and non-linear system simulations to predict degradations in the radar hardware in advance and applied the remedies to correct them. These improvements allowed for near-real-time data products to be generated by reducing the need for advanced signal processing techniques. We also developed a T-shape Mills-Cross antenna array to obtain a small overlapped footprint of transmit and receive antennas. We performed measurements over snow in Grand Mesa, Colorado, from March to April 2022, and the radar mapped the top and bottom interfaces and density changes of 1.2-2.1m of snow. We generated a snow thickness map from the data collected over the grid flown and compared results with in-situ measurements. The comparison between radar estimates and in-situ measurements shows that the average snow depths obtained from the radar data are within a standard deviation from the mean of in-situ measurements.
... Recently, drones have been used as vehicles to transport on-board sensors for various purposes (Vivow and Udawatta, 2016;Renwick et al., 2016;Shin et al., 2017;Suh et al., 2017;Dering et al., 2019;Jensen et al., 2020). It is interesting to highlight in this context the study carried out by Joseph et al. (2016) who used lightweight electronics and multiple antennas mounted on a drone to perform radio frequency (RF) measurements in the GSM 900 MHz band. ...
Personal exposimeters are currently used in studies assessing human exposure to electromagnetic fields. These devices are usually carried by an individual, but vehicles such as bicycle or car are also used. The aim of the present study was to propose a personal exposimeter attached to a drone to perform environmental radio-frequency measurements. Trials were carried out to determine whether: (i) the wireless communication between the remote controller and the drone affects the downlink mobile telephony bands by a cross-talk effect, and (ii) the structure of the drone alters the measurements of the exposimeter compared to when the meter is on a tripod. To apply this system to a real scenario, a 3D representation of the electric field in a building was obtained, and the attenuation due to the building of radiation from outside was estimated. Measurements of the electromagnetic field with this system will make it possible to monitor without risk the emissions of antennas in their close vicinity, and to validate propagation models experimentally.
... Low-frequency ultrawideband (UWB) millimeter radar has good penetration capacity and offers potential for imaging building interiors. Previous demonstrations of UAV SAR include the P, L, and C bands [212] for civil and deformation monitoring applications; X band [213] for calculating the scattering characteristics of complex targets; P and C bands for estimating the terrain height of a eucalyptus forest [214]; UWB [215] for snow coverage scanning; and W band [216] to minimize the size and weight of the hardware, among others, and different or full polarization combinations, e.g., horizontal and vertical backscatters. ...
... Low-frequency ultrawideband (UWB) millimeter radar has good penetration capacity and offers potential for imaging building interiors. Previous demonstrations of UAV SAR include the P, L, and C bands [212] for civil and deformation monitoring applications; X band [213] for calculating the scattering characteristics of complex targets; P and C bands for estimating the terrain height of a eucalyptus forest [214]; UWB [215] for snow coverage scanning; and W band [216] to minimize the size and weight of the hardware, among others, and different or full polarization combinations, e.g., horizontal and vertical backscatters. ...
Remote sensing-based forest investigation and monitoring have become more affordable and applicable in the past few decades. The current bottleneck limiting practical use of the vast volume of remote sensing data lies in the lack of affordable, reliable, and detailed field references, which are required for necessary calibrations of satellite and aerial data and calibrations of relevant allometric models. Conventional field investigations are mostly limited to a small scale, using a small quantity of observations. Rapid development in close-range remote sensing has been witnessed during the past two decades, i.e., in the constant decrease of the costs, size, and weight of sensors; steady improvements in the availability, mobility, and reliability of platforms; and progress in computational capacity and data science. These advances have paved the way for turning conventional expensive and inefficient manual forest in situ data collections into affordable and efficient autonomous observations.
... The development of technologies suited for long-range Arctic missions, such as finding shorter and safer shipping routes, geological survey for undiscovered rare earth elements, delivering medical supplies to remote areas, aquaculture inspection, Search & Rescue (SAR) operations, surveillance & reconnaissance, and tracking Arctic ice and vegetation for climate change study are important but difficult challenges [7], [8]. Unmanned Aircraft Systems (UAS/drones) is a key enabling technology for such missions in the harsh Arctic environment [9]. ...
The Arctic is one of the least developed and most under-invested regions in the world, primarily due to its harsh environment and remoteness. However, with the current retreat of Arctic sea ice, the pristine Arctic region is gradually open for economic activities and has been of great interest for Arctic council members. For example, the European Union (EU) Integrated Policy for the Arctic has a clear emphasis on the issues specific to the European Arctic. In particular, it focuses on sustainable Arctic maritime economic growth and launches a process of identifying and developing its relevant key enabling technologies. Unmanned Aircraft System (UAS) or drone is a key enabling technology for missions in harsh and remote Arctic environment, such as finding shorter and safer shipping routes, geological survey for undiscovered rare earth elements, delivering medical supplies to remote areas, Search & Rescue operations, and tracking Arctic ice and vegetation for climate change study. In this paper, we present challenges, opportunities, and enabling technologies related to the development of UAS for Arctic applications. Furthermore, we discuss our hands-on experience of flying drones in harsh Arctic environment and provide a list of operational risks and recommendations.
Airborne ground-penetrating radar systems offer a secure and time-efficient method for measuring snow depth and snowpack stratigraphy in challenging terrain with potential avalanche hazard. The SnowDrone is a custom-made snow measurement system incorporating an uncrewed aerial vehicle (UAV) platform and radar payload. Specifically designed for conducting snow surveys across diverse snow cover scenarios, this system features performance attributes tailored for such missions. Here, we present the technical implementation of the complete system, coupled with validation findings from three extensive field campaigns conducted on Svalbard. Furthermore, we provide insights into snow stratigraphy measurements obtained with the Snow-Drone, and in situ obtained snow profiles for comparative analysis. The validation is conducted by correlating the radar observations with 1673 co-located in situ measurements of snow depth, ranging from 5 to 200 cm, and revealing a high degree of agreement, yielding a correlation coefficient of r = 0.938. The SnowDrone emerges as a reliable and effective tool for assisting with local avalanche danger assessments at the slope scale, where information on snow depths and structure is crucial.
Recent advancements in drone technology have introduced new possibilities for high-density 3D and 4D ground-penetrating radar (GPR) data acquisition over alpine glaciers. In this study, we present a 4D dataset acquired over a near-terminus collapse feature at the Rhône Glacier in Switzerland. The survey covers an area of approximately 100 m x 150 m, consists of over 100 parallel GPR lines with a lateral spacing of 1 m, and was repeated four times between July and October 2022. The glacier’s rough surface made such high-resolution and high-density surveying impossible with conventional acquisition methods, highlighting the advantages of the drone-based GPR system. The GPR data provide insights into the formation of the collapse feature as well as the evolution of associated glaciological structures. Our analysis suggests that the collapse initiated where the main subglacial water channel meanders and merges with a smaller secondary channel, coinciding with a small step in bedrock topography. After initiation, the subglacial cavity expanded through a combination of ice melting and mechanical failure, with ice lamellas detaching from the cavity roof. This process led to a progressive thinning of the roof, contributing to further instability. At the surface, these subsurface processes manifested as concentric circular crevasses, ultimately culminating in the collapse of the cavity roof. The GPR measurements also reveal the rapid temporal evolution of the main subglacial channel downstream of the cavity. During the observed summer, the channel underwent significant changes in both shape and size, which we attribute to the advection of warm air from the glacier’s large portal and the resulting increase in melt at the channel walls.
This letter deals with full 3D imaging by contactless multi-monostatic Ground Penetrating Radar data by focusing on the effect of the measurement configuration on reconstruction performance. The imaging is faced as a linear inverse scattering problem and the Truncated Singular Value Decomposition is adopted to obtain the regularized solution. A criterion to determine a suitable spacing among the measurement points is provided and the effect of the data under sampling on the imaging results is also investigated. Numerical results based on the system point spread function are provided to verify the validity of the proposed criterion for the estimation of the non-redundant measurement spacing. Finally, reconstruction results relevant to a laboratory controlled experimental test validate the imaging approach as well as the derived data sampling criterion.
Mini-drone-based radar imaging is a rapidly growing research area that is gaining significant attention thanks to its potential practical applications. The focus of this chapter is on the challenges involved in the design of unmanned aerial vehicles (UAV)-based ground penetrating radar (GPR) systems to characterize the conditions of reinforced concrete structures. The chapter starts with a brief chronological review of down-looking radar imaging systems mounted on mini-drones that have been proposed so far. Then, the attention is focused on the main hardware components of UAV-based GPR systems and on a prototype designed as part of the “Monitoring Bridges with Drones” project. The main issues related to data processing are also discussed, and microwave tomography approaches recently proposed in literature are reviewed. Finally, the main challenges arising in bridge monitoring via UAV based GPR are traced, and some preliminary results are presented.
Objectives . Snow cover has a complex multifactorial impact on the environment as a link between global climatic processes and the system of the Earth’s surface. Snow cover monitoring is one of the key tasks of hydrometeorology which also requires the systematic regular collection of its indicators. This work aims to develop an architecture of geoinformation technology for snow cover monitoring with the purpose of addressing the problem of automating the collection of snow cover indicators and their further maintenance. This architecture can also be used for other hydrometeorological monitoring tasks.
Methods . This paper analyzes the existing fundamental basis of snow cover data collection and uses the method of systems approach to describe the architecture of distributed geoinformation technology.
Results . The paper presents an architecture of distributed geoinformation technology focused on snow cover monitoring from measurements, data aggregation, and validation to their transfer to a centralized processing system. A prototype of portable user terminal modules for testing this technology is developed.
Conclusions . The proposed architecture is capable of functioning in circumstances of limited telecommunication availability, while ensuring data integrity control and personalization of responsibility by introducing an electronic signature of each measurement session. This architecture can be expanded by developing and implementing modules for other types of measurements.
Recent research has highlighted the potential for high-resolution, high-density, 3D and 4D ground-penetrating radar (GPR) acquisitions on alpine glaciers. When carried out on foot, such surveys are laborious and time consuming, which limits their application to small domains of limited glaciological interest. Further, crevasses and other hazards make the data acquisition risky. To address these issues, we have developed a drone-based GPR system. The system has a payload weight of 2.2 kg and a data output rate of 14 traces per second. An 80-MHz antenna and a recording time of 2800 ns mean that depths of over 100 m can be reached in temperate ice. Differential GPS positioning assures accurate flight paths. At a speed of 4 m s ⁻¹ and height of 5 m above the glacier surface, our system can acquire over 4 line-km of GPR data in 20 min on a single set of drone batteries. After presenting the technical specifications of the system and tests required to optimize its performance, we showcase a recently acquired 3D dataset from the Otemma glacier in Switzerland, where 462 parallel GPR profiles were surveyed at a 1-m line spacing, totaling over 112 line-km of data, in only 4 days.
A talajnedvesség-tartalom variabilitásának mérését jelentősen megnehezíti a talaj heterogenitása és a környezeti változatosság. Jelenleg még nem fejlesztettek ki olyan univerzális módszert, amely a magas vagy alacsony talajnedvesség-zónák szántóföldi léptékű feltérképezésére alkalmas úgy, hogy a talajnak és a talajnedvesség áramlásának teljes zavarásmentességét nagy mélységben is biztosítja.
A talajnedvesség-mérés részben (talajkapcsolt), vagy teljesen roncsolásmentes (levegőkapcsolt) lehetőségét biztosítja a földradar (GPR), amely nagy felbontást és jelentős behatolási mélységet biztosít a közepes léptékű talajnedvesség meghatározáshoz, így hiánypótló technikát jelent a kisléptékű pontszerű és a nagyléptékű távérzékelt mérési technikák közötti metodikai hiány kitöltésére. Emellett jobb időhatékonyággal alkalmazható más roncsolásos és roncsolásmentes eljárásokkal összevetve.
A talajradart sikeresen alkalmazták a talajnedvesség-meghatározásra, de hidrológiai vizsgálatokban történő alkalmazásának nagy potenciálja ellenére nem minden körülmény között működik optimálisan. Felhasználhatósága többnyire olyan területekre korlátozódik, ahol viszonylag alacsony az elektromos vezetőképesség (az elektromágneses hullám gyenge csillapodására való tekintettel). Ezen túlmenően egyes talajradar módszerek működésének alapfeltétele a jól azonosítható és folyamatos jelvisszaverődés, továbbá a dielektromos állandó tekintetében a földradar-rendszerek térben folyamatos felszín alatti kontrasztot igényelnek.
A talajnedvesség és annak áramlása kulcsparaméter a mezőgazdaság különböző területein. A talajnedvesség (és a talajvíz) látja el a növényeket, ami elengedhetetlen feltétele a növények fejlődésének. Ennélfogva a talaj nedvességtartalmának, eloszlásának, áramlásának, valamint a beszivárgás sajátosságainak alapos és lokális ismerete az öntözés hatékony megvalósításának alapköve, különösen a félszáraz és száraz éghajlatú területeken.
A talajradar mérési alapjaival, valamint hasznosítási lehetőségeivel összefüggésben az elsősorban nemzetközi szakirodalmat összegezve megállapítható, hogy a GPR előnyös mérőeszköz lehet, amely segíthet a talaj nedvességeloszlásának feltérképezésében, tekintettel a beszivárgásra, a párolgás és a növényi vízfelvétel okozta vízveszteségre is. Következésképpen mezőgazdasági felhasználhatósága lehetséges.
A talajradar hasznos része lehet a „Smart farming”-nak (intelligens gazdálkodás), segítséget nyújthat a talajban elhelyezett talajnedvesség-mérő szenzorok kijelölésében. Különösen, ha a közelmúltban megjelent új, szimultán többeltolásos és többcsatornás (SiMoc) GPR rendszerre asszociálunk, amely gyors talajprofil-feltérképezést tesz lehetővé a hét vevőegységével, de a hagyományos egycsatornás GPR sebességével.
Ha a teljes roncsolásmentesség a cél, úgy a drónra szerelt levegőkapcsolt GPR-ek nyújthatnak lehetőséget. Megjegyzendő azonban, hogy a talaj-levegő határfelületen jelentkező szignifikáns jelcsillapodás (hullámszóródás) következtében a feltárási mélység jelentősen csökken.
A földradar végső soron mérési alapul szolgálhat a hatékony (precíziós) öntözési gazdálkodás kialakításához, és a megfelelő vízfelhasználási hatékonyságot biztosítva járulhat hozzá a precíziós mezőgazdasági programok megvalósításához.
Current methods of snowpack stability assessment primarily rely on professional observations, mainly digging a snow pit. This technique has spatial limitations, is time-consuming, and places observers at risk. The combined usage of UAVs and GPR is capable of providing detailed snowpack layering data at scale without human exposure to potential avalanche-prone areas. The presented study aims to obtain radargrams of the study area's internal snowpack layering structure. A single-channel GPR with a 1000 MHz shielded antenna is attached to a UAV to survey the snowpack. The UAV flights are carried out semi-automatically from a safe spot at a speed of 1 m/s at a LiDAR altimeter-adjusted distance to the snow surface of 5 m. The data obtained by the GPR is then compared to density measurements and manual snowpack observations following international standards. The preliminary results indicate the success of the UAV's flight performance and the accuracy of the GPR data in determining the snow depth and detecting the most prominent layers of the snowpack.
Unmanned aerial vehicles (UAVs) are expected to be used extensively in the future for various applications, either as user equipment (UEs) connected to a cellular wireless network, or as an infrastructure extension of an existing wireless network to serve other UEs. Next generation wireless networks will consider the use of UAVs for joint communication and radar and/or as dedicated radars for various sensing applications. Increasing number of UAVs will naturally result in larger number of communication and/or radar links that may cause interference to nearby networks, exacerbated further by the higher likelihood of line-of-sight signal propagation from UAVs even to distant receivers. With all these, it is critical to study network coexistence of UAV-mounted base stations (BSs) and radar transceivers. In this paper, using stochastic geometry, we derive closed-form expressions to characterize the performance of coexisting UAV radar and communication networks for spectrum overlay multiple access (SOMA) and time-division multiple access (TDMA). We evaluate successful ranging probability (SRP) and the transmission capacity (TC) and compare the performance of TDMA and SOMA. Our results show that SOMA can outperform TDMA on both SRP and TC when the node density of active UAV-radars is larger than the node density of UAV-comms.
This study aims to investigate the layer structure within an alpine snowpack using UAV-borne GPR. Weak layers are the target of this survey as they are relevant with regards to the formation of slab avalanches, being the most frequent type of avalanche when it comes to avalanche fatalities and infrastructural damage. The main goal is to evaluate this innovative approach through several field campaigns where both airborne GPR data and manual snow pit observations including stability tests are acquired. The data are then compared to assess the feasibility of this method to detect weak layers within the snowpack, and its suitability to contribute to quality enhancement in avalanche forecasting and monitoring is critically evaluated. Application is also assumed to be successful for infrastructural avalanche monitoring purposes, e.g., along roads and railways, or to assess slope stability in case of freeride contests to minimize risk for professional riders. In a future, more mature state of the research project, it is aimed to automatically analyze the remotely acquired GPR data.
Due to the increasing number of aerial radars and joint communication/sensing technologies, interference from uncoordinated radars will limit the target detection and ranging performance in the future. In this paper, we investigate the interference behavior in an aerial radar network for sensing ground targets. We consider that the radars mounted on unmanned aerial vehicles (UAVs) that fly at a certain altitude are randomly distributed according to a two-dimensional homogeneous Poisson point process (HPPP), and that the propagation is modeled using a probabilistic line-of-sight (LoS) channel model. For such a sensing network, we derive the distribution of the radar interference using a stochastic geometry based analysis. In particular, when Swerling I model is considered for radar cross-section area (RCS) for the target, we derive the Laplace transform of the radar interference. To avoid a strong interference between neighboring radars, a guard zone is introduced within which the UAV radar transmission around the permitted active radar is inhibited. As the radar performance metric, we derive the successful ranging probability (SRP) of a given radar by exploiting the Laplace transform of radar interference. Using the analytic SRP, we show that we can optimize the radar network parameters such as the radius of the guard zone and the density of the active radars. In addition, we also discuss how the analytic SRP gives an insight into the spectrum utilization strategy for the UAV radar networks with the guard zones.
The field of multicopter unmanned aerial vehicles (UAVs) has seen massive technological advances and decreasing costs over the last decade. Due to the higher prevalence and availability of these multicopter UAVs, there have also been rapid improvements in the software interfaceability, enabling the easy integration of custom software for flight planning and controllers. This opened up completely new possibilities, such as low-cost individual aerial photography, the most common civilian application. Furthermore, lightweight multicopters became widely accessible to the public, boosting the development of UAVs even more.
Nowadays, the ultrawideband (UWB) has become a popular solution to the indoor localization problem of quadrotor unmanned aerial vehicle (UAV) due to its low power consumption and ease of implementation. Nonetheless, the accuracy of UAV localization is affected by the skew-
t
measurement noises of the UWB sensor induced mainly by the nonline-of-sight (NLOS) errors and the multipath effects, and the uncertainties in the UAV dynamics caused by external wind disturbances. In this article, a composite filtering approach is proposed for time difference of arrival (TDOA)-based UWB localization of the quadrotor UAV. The main advantage of the composite filtering approach lies in its capability of dealing with the skew-
t
measurement noises and the dynamic uncertainties simultaneously. Specifically, the external winds are estimated and rejected in real time via the disturbance observer (DO). Meanwhile, the posterior state distribution under skew-
t
measurement noises is updated in an iterative fashion within the variational Bayes (VB) framework. The effectiveness of the proposed approach is validated through both numerical simulation and experimental tests on a quadrotor UAV.
MonitoringMonitoring efforts for remote high-latitude and high-altitude glacierized regions heavily rely on remote sensingRemote sensing. Rapid ongoing changes in polarPolar and cryosphericCryosphere environments owing to contemporary climate changeClimate change have attracted more attention towards these regions than ever before. Satellite Satellitesremote sensingRemote sensing has its own limitations related to low sun angles in high latitudes, high acquisition costs for high-resolution images, and persistent cloud cover over ice-dominated land and oceanOceans surfaces. As such, over the past several years, small unoccupied aerial systems (sUAS)Small unoccupied aerial systems (sUAS) have become a viable data collection tool to address the challenges related to spaceborne or expensive airborne remote sensingRemote sensing for monitoringMonitoring the cryosphereCryosphere and polarPolar regions. This chapter discusses sUASSmall unoccupied aerial systems (sUAS) adaptations for collecting data on snowSnow, glaciers, permafrostPermafrost, polarPolar biology, the oceanOceans, and atmosphereAtmosphere; the challenges of conducting sUASSmall unoccupied aerial systems (sUAS) operations in polarPolar latitudes; and the advantages and disadvantages of the technology. It also provides resources that can be used to guide future efforts in applying sUASSmall unoccupied aerial systems (sUAS) to polar and Polarcryospheric researchCryosphere.
Advances in unmanned aerial vehicle (UAV) technology have fostered its use in a wide range of areas, such as agriculture and forestry, surveillance and security, and infrastructure inspection. One of the advantages of UAVs is their ability to conduct remote inspection and sensing by placing different kinds of sensors on board them. In this sense, UAV-based ground-penetrating radar (GPR) systems are of particular interest as they bring together the advantages of UAVs and GPR, resulting in contactless subsurface sensing and imaging systems capable of performing a fast scanning of difficult-to-access scenarios. This contribution reviews the advances on UAV-based GPR systems, describing their architecture and subsystems. In particular, an analysis of different UAV-based GPR systems is presented, focusing on the technical solutions adopted in each case and the detection capabilities that have been achieved. Attention will be also given to the methodologies implemented to obtain 3D high-resolution images of the underground. Finally, the main challenges faced by these systems concerning further improvements of the scanning throughput and the detection accuracy will be discussed.
Airborne synthetic aperture radar (SAR) sensors have been commonly used during the last decades to monitor different phenomena in medium-scale areas of observation, such as object detection and characterization or topographic mapping. The use of unmanned aerial vehicles (UAVs) is a cost-effective solution that offers higher operational flexibility than airborne systems to monitor these types of scenarios. The Universitat Politècnica de Catalunya has developed the first fully polarimetric SAR system at X-band integrated into a small UAV multicopter platform (UAV MP). The sensor, called AiR-based remote sensing, has been integrated into the platform overcoming restrictions of weight, space, robustness, and power consumption. To demonstrate the validity of the developed system, some measurement campaigns have been conducted in the outskirts of Barcelona, Spain.
High-resolution, downward-looking radar imaging is demonstrated using a small consumer drone. The entire system including an ultra-wideband radar, antennas, camera, and a single-board computer fits on a small drone and is controlled through a Wi-Fi connection. The drone-fitted system is able to collect concurrent radar and video data of the same scene. The measurement results of three real-world settings (trees, parked vehicles, and humans) are presented and discussed.
Synthetic aperture radar (SAR) imaging is demonstrated using a small consumer drone. The entire imaging system including an ultra-wideband radar, antennas, and a single-board computer fits on a small drone and is controlled through a Wi-Fi connection. Motion compensation is carried out based on a prominent scatterer algorithm. The focused SAR image of four trihedrals is validated against simulation. Measured SAR images of a human and a car are also presented.
In this paper, a tapered slot antenna capable of ultra-wideband communication was designed. In the proposed antenna, rectangular slits were inserted to enhance the bandwidth and reduce the area of the antenna. The rectangular slit-inserted tapered slot antenna operated at a bandwidth of 8.45 GHz, and the bandwidth improved upon the basic tapered slot antenna by 4.72 GHz. The radiation pattern of the antenna was suitable for location recognition in a certain direction owing to an appropriate 3 dB beam width. The antenna gain was analyzed within the proposed bandwidth, and the highest gain characteristic at 7.55 dBi was exhibited at a 5-GHz band. The simulation and measurement results of the proposed tapered slot antenna were similar.
The complex dielectric constant of snow has been measured at microwave frequencies. New and old snow at different stages of metamorphosis have been studied. The results indicate that the complex dielectric constant is practically independent of the strncture of snow. For dry snow, the dielectric constant is determined by the density. For wet snow, the imaginary part and the increase of the real part due to liqnid water have the same volumetric wetness dependence. The frequency dependence of the complex dielectric constant of wet snow is the same as that of water. A nomograph for determining the density and wetness of wet snow from its dielectric constant is given. A snow sensor for fielmd easurement of the dielectric constant has been developed. It can be used for determining the density and the wetneosfs snow bya singlem easurement.
The stratigraphy of an alpine snowpack is very important for avalanche danger assessment, as well as interpretation of remote sensing measurements for hydrological purposes. Since spatial variability is often widespread, due mainly to wind, micro-climatic and topographic effects, extrapolating point measurements can be difficult. Tools which can quickly characterize snowpack stratigraphy, such as high frequency radar and mechanical probes, will be required for a complete understanding of the effects of spatial variability, however interpretation of these kinds of measurements still remains challenging. We compare measurements from a portable 8–18 GHz Frequency Modulated Continuous Wave (FMCW) radar with SnowMicroPenetrometer (SMP) and standard snowpit measurements. Although significant variability existed at the sub-meter scale, major stratigraphic horizons could be followed along radar profiles and identified in SMP measurements. A very thin hard crust (0.2–0.4 mm) that was continuous caused strong signals that were identifiable in both the SMP and the radar measurements at five different sites along a 10 m traverse. Two other more subtle transitions in the SMP signal were highly correlated with the locations of radar reflections. This work suggests that combining FMCW radar measurements, to characterize snowpack geometry, with SMP measurements, to characterize mechanical properties of layers, may be a useful technique for quantifying the spatial variability of the snowpack.
During the spring of 2009, an ultrawideband microwave radar was deployed
as part of Operation IceBridge to provide the first cross-basin surveys
of snow thickness over Arctic sea ice. In this paper, we analyze data
from three ˜2000 km transects to examine detection issues, the
limitations of the current instrument, and the regional variability of
the retrieved snow depth. Snow depth is the vertical distance between
the air-snow and snow-ice interfaces detected in the radar echograms.
Under ideal conditions, the per echogram uncertainty in snow depth
retrieval is ˜4-5 cm. The finite range resolution of the radar
(˜5 cm) and the relative amplitude of backscatter from the two
interfaces limit the direct retrieval of snow depths much below ˜8
cm. Well-defined interfaces are observed over only relatively smooth
surfaces within the radar footprint of ˜6.5 m. Sampling is thus
restricted to undeformed, level ice. In early April, mean snow depths
are 28.5 ± 16.6 cm and 41.0 ± 22.2 cm over first-year and
multiyear sea ice (MYI), respectively. Regionally, snow thickness is
thinner and quite uniform over the large expanse of seasonal ice in the
Beaufort Sea, and gets progressively thicker toward the MYI cover north
of Ellesmere Island, Greenland, and the Fram Strait. Snow depth over MYI
is comparable to that reported in the climatology by Warren et al.
(1999). Ongoing improvements to the radar system and the utility of
these snow depth measurements are discussed.
An investigation was made to estimate the variance, measurement errors and sampling error in currently accepted practices for manual snow density measurement carried out as part of snow profile observations using the available variety of density cutters. A field experiment in dry snow conditions was conducted using a randomized block design to account for layer spatial variability. Cutter types included a 500 cm3 aluminium tube, 200 and 100 cm3 stainless-steel box types, 200 cm3 stainless-steel wedge types and a 100 cm3 stainless-steel tube. Without accounting for variation due to weighing devices, the range of values for 'accepted practice' determined in this study included variation within individual cutters of 0.8-6.2%, variation between cutters of 3-12%, variation between cutter means and layer means of 2-7%, and under-sampling errors of 0-2%. The results of a statistical analysis suggest that snow density measurements taken using various density cutters are significantly different from each other. Without adjustment for under-sampling, and given that the mean of all measurements is the accepted true value of the layer density, variation exclusively between cutter types provides 'accepted practice' measurements that are within 11% of the true density.
Ultra-wideband (UWB) sensing is an upcoming technique to gather data from complex scenarios such as nature, industrial facilities, public or private environments, for medical applications, non-destructive testing and many more. Currently it is hard to estimate the full spread of future applications. The measurement approach traditionally used is based on stimulation of the test objects by either short sub-nanosecond impulses or sine waves which are stepped/swept over a wide spectral band. This paper deals with an alternative approach, which uses very wideband pseudo-noise binary signals such as M-sequences for example. Such devices have a very high time stability, enable high measurement speed and do not burden the test objects with high voltage peaks. Furthermore, the device concept promotes monolithic circuit integration in a low cost semi-conductor technology. In what follows, the basic device concept and some extensions will be considered as well as some selected applications will be discussed.
The pioneers of radio science made their first trials of wireless information transmission and demonstrated localization of a steel vessel by radio waves more than 100 years ago. Back then, the world of radio frequencies was organized in a very simple way. The researchers could use any frequency band. There was no interference by others and no controlling government bodies. Since then, governmental authorities have established tight regulations that have split up the available frequency band into small partitions for exclusive use. This article discusses the architecture of a baseband, pseudo-noise UWB radar and gives some examples of applications
This paper presents a Ku-band (14-16 GHz) CMOS frequency-modulated continuous-wave (FMCW) radar transceiver developed to measure dry-snow depth for water management purposes and to aid in retrieval of snow water equivalent. An on-chip direct digital frequency synthesizer and digital-to-analog converter digitally generates a chirping waveform which then drives a ring oscillator-based Ku-Band phase-locked loop to provide the final Ku-band FMCW signal. Employing a ring oscillator as opposed to a tuned inductor-based oscillator (LC-VCO) allows the radar to achieve wide chirp bandwidth resulting in a higher axial resolution (7.5 cm), which is needed to accurately quantify the snowpack profile. The demonstrated radar chip is fabricated in a 65-nm CMOS process. The chip consumes 252.4 mW of power under 1.1-V supply, making its payload requirements suitable for observations from a small unmanned aerial vehicle.
Ground Penetrating Radar (GPR) of antenna frequency 1000 MHz was used for snow depth estimation and snow stratigraphic studies in the Pir Panjal and Greater Himalayan range of NW Himalayas. GPR profiles were acquired at a selected site near Solang observatory (Himachal Pradesh (HP), India) for snow depth estimation. It was observed that the estimated snow depth correlates well with ground measurements taken using snow stakes. Based on these snow depth measurements with GPR and manual density measurement at different locations within the sampling area, the snow water equivalent was also estimated. Experiments were also conducted at Patseo (HP) for snow depth estimation and snowpack layer identification. By analysing the profiles we were able to capture the prominent snow layers present within the snowpack at Patseo. Manual stratigraphy was also performed along with the GPR profiles, and it was found that layer positions in the radargram correspond fairly well with the stratigraphic layer positions. Dielectric constant of snow, which is an important parameter for acquisition/interpretation of GPR profiles was also measured using snow fork.
In this paper, a realization of archimedes spiral antenna for a Radar detector is presented, where this Radar detectors are used to detect Radar signal transmission within the frequency range of 2-18 GHz. In this research, an antenna was designed for the above information band. Multiple frequency bands covered by this antenna S band (2-4 GHz), C band (4-8 GHz), X band (8-12 GHz) and Ku band (12-18 GHz). The designed antenna has a shape of a spiral with a diameter of 5 cm. The antenna was implemented on a Roger Duroid 5880 substrate with εr = 2.2, thickness of 0.787 mm, and 1 oz for copper cladding. These spiral antennas have ultra wideband characteristics due to the planar structure and circular polarization with impedance of 188 Ohm. From the simulation results of the designed antenna, we obtained VSWR of 1.1 up to 1,27, a gain ranging from 3 to 6 dBi, with 3dB bandwidth of 61.7 degree. There is a similarity between the measurements and the simulation results. The realized antennas show advantages, e.g., VSWR <;2 and high gain, compared which the existing antennas in the market.
This paper presents a radar sensor package specifically developed for wide-coverage sounding and imaging of polar ice sheets from a variety of aircraft. Our instruments address the need for a reliable remote sensing solution well-suited for extensive surveys at low and high altitudes and capable of making measurements with fine spatial and temporal resolution. The sensor package that we are presenting consists of four primary instruments and ancillary systems with all the associated antennas integrated into the aircraft to maintain aerodynamic performance. The instruments operate simultaneously over different frequency bands within the 160 MHz-18 GHz range. The sensor package has allowed us to sound the most challenging areas of the polar ice sheets, ice sheet margins, and outlet glaciers; to map near-surface internal layers with fine resolution; and to detect the snow-air and snow-ice interfaces of snow cover over sea ice to generate estimates of snow thickness. In this paper, we provide a succinct description of each radar and associated antenna structures and present sample results to document their performance. We also give a brief overview of our field measurement programs and demonstrate the unique capability of the sensor package to perform multifrequency coincidental measurements from a single airborne platform. Finally, we illustrate the relevance of using multispectral radar data as a tool to characterize the entire ice column and to reveal important subglacial features.
Now-a-days there has been growing interest in dual-pol systems, especially in hybrid-pol mode. In comparison to quad-pol system, the dual-pol system has the advantage of halved average transmitted power and double swath coverage. In this paper, we have discussed, in brief, the benefits of using hybrid-pol scheme. We also present comparisons of hybrid-pol and Quad-pol data based on the amount of information content. The airborne multi-polarization GTRI data set is used for demonstration.
In article was researched, the possibility of improving the characteristics of Vivaldi antenna by use of printed lens located in aperture. It is shown that use of lens leads to increase in gain and reduce level of side lobes. © 2014 Wiley Periodicals, Inc. Microwave Opt Technol Lett 56:369–371, 2014
Cited By (since 1996):47, Export Date: 1 December 2013, Source: Scopus
We describe a prototype ultrawideband radar. We show how the system was designed and how the hardware was developed for the radar prototype. Waveform generation, radar parameters, and signal processing for the stepped frequency waveform are discussed. The radar operates from 500 MHz to 3 GHz with a nominal resolution of 6 cm in air. The advantage of the stepped frequency approach over an impulse radar is better matching between the transmitted waveform and the receiver. We use range gating to improve the system dynamic range. The advantages are illustrated with laboratory measurements and field measurements from glacial ice and permafrost in Svalbard, showing penetration depths of 11 m. Antennas which do not require contact with the ground were developed and used in the experiments.
Snow depth was measured with an L-band frequency-modulated continuous wave (FMCW) radar operating from an aerial tramway up to 70 m above the ground. Snow depth, wetness, and slope varied greatly along the 2.4-km transect, with 640 m of relief. Radar measurements taken in the morning, when the snowpack was frozen were compared against concurrent manual depth probes, and good agreement was found between the estimates. The results suggest that deep snowpacks in rugged terrain can be accurately and safely surveyed by helicopter-borne radar.
The fundamental principles of radar backscattering measurements are presented, including measurement statistics, Doppler and pulse discrimination techniques, and associated ambiguity functions. The operation of real and synthetic aperture sidelooking airborne radar systems is described, along with the internal and external calibration techniques employed in scattering measurements. Attention is given to the physical mechanisms responsible for the scattering emission behavior of homogeneous and inhomogeneous media, through a discussion of surface roughness, dielectric properties and inhomogeneity, and penetration depth. Simple semiempirical models are presented. Theoretical models involving greater mathematical sophistication are also given for extended ocean and bare soil surfaces, and the more general case of a vegetation canopy over a rough surface.
An accurate knowledge of snow thickness and its variability over sea ice is crucial in determining the overall polar heat and freshwater budget, which influences the global climate. Recently, algorithms have been developed to extract snow thicknesses from satellite passive microwave data. However, validation of these data over the large footprint of the passive microwave sensor has been a challenge. The only method used thus far has been with meter sticks during ship cruises. To address this problem, we developed an ultrawideband frequency-modulated continuous-wave radar to measure the snow thickness over sea ice. We synthesized a very linear chirp signal by using a phase-locked loop with a digitally generated chirp signal as a reference to obtain a fine-range resolution. The radar operates over the frequency range from 2-8 GHz. We made snow-thickness measurements over the Antarctic sea ice by operating the radar from a sled in September and October 2003. We performed radar measurements over 11 stations with varying snow thicknesses between 4 and 85 cm. We observed an excellent agreement between radar estimates of snow thickness with physical measurements, achieving a correlation coefficient of 0.95 and a vertical resolution of about 3 cm. Comparison of simulated radar waveforms using a simple transmission line model with the measurements confirms our expectations that echoes from snow-covered sea ice are dominated by reflections from air-snow and snow-ice interfaces.
Conical spiral antennas can have an input impedance and gain that are nearly frequency independent over a wide bandwidth. However, these antennas normally have dispersive properties that produce significant distortion when they are used to radiate a pulse. We examine this dispersion in detail and the possibility of compensating for the dispersion so that the antenna can be used for pulse radiation. First, a simple, qualitative model for this antenna is described. This model provides physical insight into the causes for the dispersion. Next, the antenna is examined using an accurate, full electromagnetic analysis done with the finite-difference time-domain method. Results from this analysis support the conclusions reached with the simple model and provide additional insight into the dispersion. Finally, an approach for compensating for the dispersion in the antenna is described, and the interesting features of the pulse radiated from this antenna, after compensation, are discussed.
Development of an unmanned aircraft mounted software defined ground penetrating radar
- J F Fitter
- A B Mccallum
- J X Leon
J. F. Fitter, A. B. Mccallum, and J. X. Leon, "Development of an
unmanned aircraft mounted software defined ground penetrating radar,"
in Proc. 5th Int. Conf. Geotech. Geophys. Site Characterisation, vol. 5,
2016, pp. 957-962.
Snow Stratigraphy Measurements With UWB Radar
- R.-O R Jenssen
R.-O. R. Jenssen. (2016). Snow Stratigraphy Measurements With UWB
Radar. [Online]. Available: http://hdl.handle.net/10037/11117
Potential of microwave remote sensing for assessing critical snow properties
- C Mätzler
C. Mätzler, "Potential of microwave remote sensing for assessing critical
snow properties," in Proc. Workshop Adv. Techn. Assessment Natural
Hazards Mountain Areas, Innsbruck, Austria, 2000, pp. 38-41.
Development of an unmanned aircraft mounted software defined ground penetrating radar
- fitter
Snow, Weather, and Avalanches: Observation Guidelines for Avalanche Programs in the United States
- E Greene
- K Birkeland
- K Elder
- I Mccammon
- M Staples
- D Sharaf
The complex dielectric constant of snow at microwave frequencies
- M E Tiuri
- A H Sihvola
- E Nyfors
- M Hallikaiken