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Two-Stage Overlapping Algorithm for Signal Doppler Frequency Location Method
Abstract
Localization techniques of radio emitters are widely used in civil and military applications. In civilian systems, the positioning of user equipment in mobile networks is one of the basic functionalities on which many modern telecommunications services are based. In military systems, the location of radio emitters is one of the main tasks performed by reconnaissance and electronic warfare systems. For these latter, the signal Doppler frequency (SDF) method was developed. SDF allows the emitter localization by a single sensor. In this method, the radio signal processing technique is based on an overlapping algorithm, which was introduced two years ago. In this paper, we present a novel two-stage overlapping algorithm, which relates to the processing of IQ radio signal samples and then to a data vector with determined Doppler frequency shift values. The proposed solution ensures greater accuracy in positioning the emitter using the SDF.
... We propose its use at two levels of data processing, i.e., determining the DFS based on the spectra of signal samples, and estimating the emitter position using the SDF based on the DFS vector. We addressed this topic, although in a much narrower scope, in [22]. In that case, the application of overlapping focused primarily on the DFS vector level. ...
... In this case, using an overlapping factor of less than 50% may bring the expected results. The initial concept of the two-level overlapping algorithm in the SDF method was described in [22]. However, in that analysis, certain aspects were limited-no filtering was applied, only full Doppler curve variability was considered, and the overlap factor at the signal sample level was equal to 100%. ...
... This is due to the fact that increasing the increases the DFS variability range, which translates into a reduction in localization errors in the SDF. In theory, the best results can be obtained for the full Doppler curve variability (see [22]). However, considering the practical aspects of measurements, a long acquisition time can contribute to the appearance of additional errors resulting from the frequency instability of the Tx or Rx (see [21]), the movement of localized objects (see [8]), or changes in the Rx flight parameters (e.g., speed, trajectory). ...
The localization of radio emitters is a fundamental task in reconnaissance systems, and it has become increasingly important with the evolution of mobile networks. The signal Doppler frequency (SDF) method, developed for dual-use applications, leverages Doppler frequency shifts (DFSs) in received signals to estimate the positions of radio transmitters. This paper proposes enhancements to the SDF method through advanced signal processing techniques, including dedicated filtering and a novel two-level overlapping approach, which significantly improve localization accuracy. The overlapping technique increases the number of DFS estimations per time unit by analyzing overlapping segments at both the signal sample level and within the DFS vector. Simulation studies using various filter types and overlapping parameters were conducted to evaluate the effectiveness of these enhancements in a dynamic scenario involving multiple stationary transmitters and a single moving receiver. The results demonstrate that the proposed approach minimizes localization errors. The application of low-pass filtering at the DFS vector level improves localization accuracy. In the study, three types of filters for different cutoff frequencies are considered. Each of the analyzed filters with an appropriately selected cutoff frequency provides a comparable reduction in localization error at the level of about 30%. The use of overlapping at the signal sample level with a factor of 10% allows for more than a twofold decrease in localization errors, while overlapping at the DFS vector provides an increase in the refresh rate of the position of localized objects. Comparative analysis with direct position determination techniques additionally showed high effectiveness of the SDF method, especially using data filtration and overlapping. The simulation studies carried out are of significant importance for the selection of the operating parameters of real localization sensors in unmanned aerial vehicle (UAV) equipment.
... Under this grant, UAVs carrying out COMINT tasks in the field of spectrum monitoring and locating radio emitters will be developed. For the second task, we plan to use a Doppler-based localization method called the signal Doppler frequency (SDF) [27,28]. On the other hand, the localization of radio emitters is widely used in the civil market, including, among others, in positioning wireless network users or users who illegally use licensed frequency bands. ...
... Measurements [30] have shown that using ground vehicles introduces limitations to the localization procedure, including difficulties in maintaining a constant speed, changing the sensor motion direction, and multipath propagation resulting from the neighborhood of terrain obstacles [32]. The use of UAVs [27,28] or watercrafts [33] for this purpose provides greater opportunities, provides greater movement freedom, and improves propagation conditions by minimizing the impact of unfavorable phenomena. ...
... This effect translates into larger localization errors for the long-range case. Therefore, when planning the mission, the appropriate direction of the sensor movement trajectory should be considered [27,33], or the value of the signal acquisition window should be adjusted [28]. ...
In this paper, we explore several widely available software-defined radio (SDR) platforms that could be used for locating with the signal Doppler frequency (SDF) method. In the SDF, location error is closely related to the accuracy of determining the Doppler frequency shift. Therefore, ensuring high frequency stability of the SDR, which is utilized in the location sensor, plays a crucial role. So, we define three device classes based on the measured frequency stability of selected SDRs without and with an external rubidium clock. We estimate the localization accuracy for these classes for two scenarios, i.e., short- and long-range. Using an external frequency standard reduces the location error from 20 km to 30 m or 15 km to 2 m for long- and short-range scenarios, respectively. The obtained simulation results allowed us to choose an SDR with appropriate stability. The studies showed that using an external frequency standard is necessary for minimizing SDR frequency instability in the Doppler effect-based location sensor. Additionally, we review small-size frequency oscillators. For further research, we propose two location sensor systems with small size and weight, low power consumption, and appropriate frequency stability. In our opinion, the SDF location sensor should be based on the bladeRF 2.0 micro xA4 or USRP B200mini-i SDR platform, both with the chip-scale atomic clock CSAC SA.45s, which will allow for minor positioning errors in the radio emitters.
... • The location sensor estimated the instantaneous DFS every 1 s. Based on the research in [12], we set the acquisition time of 8 9 = 30s for SRS and 300s for LRS and therefore the emitter coordinates were estimated every 1 s based on 30 and 300 DFSs. ...
This paper focuses on testing the suitability of the USRP B200mini platform for radio emitter localization using the Signal Doppler Frequency (SDF) method. We show how to emulate the Doppler effect in laboratory conditions for different scenarios. For each scenario, we estimate the localization accuracy. We compare our measurement results with simulation studies.
... Localization of modulated signals using the SDF method implemented on a single UAV is presented in [35]. A two-stage overlapping algorithm for SDF location methods is presented in [36]. The future research work using UAS will be devoted to studies related to the accuracy of localization by the SDF method under the variable speed of the moving survey platform. ...
The article presents the first implementation of the Signal Doppler Frequency (SDF) location method on an Unmanned Aerial Vehicle (UAV) named Autonomous System of Location radio EmmiteRs (ASLER), employing a DJI Matrice UAV as its mobile platform for the radio sensor. The system is used for position estimation, i.e., determining the location coordinates of localized radio emitters. Such functionality is the basis of radio reconnaissance, electronic warfare, or combat systems, and many radio navigation systems. The ASLER localization procedure is based on the Doppler localization method, also known as the SDF. Its distinctive feature is the use of a single moving platform for localization. In addition, the SDF allows simultaneous localization of multiple emission sources, which is an innovative distinction compared to other solutions of this class. ASLER is the first autonomous implementation of the SDF method on a flying platform. This paper illustrates the hardware and software implementation of location sensor, and results of the first empirical studies.
... An example measurement is depicted in Figs. 2 and 3. The collected DFSs are filtered and averaged [9], and then the selected range of them is subjected to mathematical calculations according to (2) to obtain , coordinate results. ...
This paper presents the results of the firstlocalization measurements of a radio transmitter emittingmodulated signals (e.g., binary and quadrature phase-shift keyingor quadrature amplitude modulation) using the Signal DopplerFrequency (SDF) method implemented on a single flyingmeasurement platform. The SDF method is an innovativelocalization method based on the variation of the Doppler curve,the shape of which is characteristic of the mutual position of thetransmitter relative to the receiver trajectory or vice versa. Thismethod could commonly use to determine the position of variousradio transmitters. Currently, we are testing the firstimplementation of this method on unmanned aerial vehicle.
... An example measurement is depicted in Figs. 2 and 3. The collected DFSs are filtered and averaged [9], and then the selected range of them is subjected to mathematical calculations according to (2) to obtain , coordinate results. ...
This paper presents the results of the first localization measurements of a radio transmitter emitting modulated signals (e.g., binary and quadrature phase-shift keying or quadrature amplitude modulation) using the Signal Doppler Frequency (SDF) method implemented on a single flying measurement platform. The SDF method is an innovative localization method based on the variation of the Doppler curve, the shape of which is characteristic of the mutual position of the transmitter relative to the receiver trajectory or vice versa. This method could commonly use to determine the position of various radio transmitters. Currently, we are testing the first implementation of this method on unmanned aerial vehicle.
This paper focused on assessing the effectiveness of the signal Doppler frequency (SDF) method to locate a mobile emitter using a swarm of unmanned aerial vehicles (UAVs). Based on simulation results, we showed the impact of various factors such as the number of UAVs, the movement parameters of the emitter and the sensors on location effectiveness. The study results also showed the dependence of the accuracy and continuity of the emitter coordinate estimation on the type of propagation environment, which was determined by line-of-sight (LOS) or non-LOS (NLOS) conditions. The applied research methodology allowed the selection of parameters of the analyzed location system that would minimize the error and maximize the monitoring time of the emitter position.
In order to synthesize the noise of internal combustion engines at arbitrary speed variations, an overlap-add-based method is proposed to be applied to sound samples extracted from a prerecorded engine noise at a continuously-varying speed. The objective of this new method is to minimize the phase discontinuities between a finite number of harmonics of the sample sounds likely to be concatenated. The harmonicity of the synthesized signal is then preserved which greatly enhances the acoustic quality of the restitution. Moreover, the synthesis stage is well suited for real time applications due to a low computational load compared to existing approaches. The proposed analysis-synthesis method can be applied to any harmonic sound whose spectral content depends solely on its fundamental frequency. By analogy to existing overlap-and-add methods, the method introduced here is referred to as Harmonic Synchronous Overlap and Add (HSOLA).
The unique characteristic of bandwidth-distance relationship in underwater acoustic (UWA) channels makes standard uplink non-orthogonal multiple access (NOMA) scheme not be applicable in general underwater acoustic networks (UWANs). In this paper, we propose an uplink partial overlapping non-orthogonal multiple access (PONOMA) scheme for UWANs, and investigate capacity region of uplink PONOMA in UWANs. By formulating the problem of the optimal energy distribution for uplink PONOMA based on UWA channel modeling, the closed-form solutions for optimal power spectral density (p.s.d.) and capacity region are derived. Furthermore, we modify the channel modeling by building in parameter uncertainty induced by the empirical nature of UWA channel modeling using box sets, and derived robust capacity region under parameter uncertainty. Numerical results are provided to demonstrate the performance of our proposed scheme.
The rapid development in various fields of Digital Audio Effects, or DAFX, has led to new algorithms and this second edition of the popular book, DAFX: Digital Audio Effects has been updated throughout to reflect progress in the field. It maintains a unique approach to DAFX with a lecture-style introduction into the basics of effect processing. Each effect description begins with the presentation of the physical and acoustical phenomena, an explanation of the signal processing techniques to achieve the effect, followed by a discussion of musical applications and the control of effect parameters. Topics covered include: filters and delays, modulators and demodulators, nonlinear processing, spatial effects, time-segment processing, time-frequency processing, source-filter processing, spectral processing, time and frequency warping musical signals. Updates to the second edition include: • Three completely new chapters devoted to the major research areas of: Virtual Analog Effects, Automatic Mixing and Sound Source Separation, authored by leading researchers in the field. • Improved presentation of the basic concepts and explanation of the related technology. • Extended coverage of the MATLABTM scripts which demonstrate the implementation of the basic concepts into software programs. • Companion website (www.dafx.de) which serves as the download source for MATLABTM scripts, will be updated to reflect the new material in the book. Discussing DAFX from both an introductory and advanced level, the book systematically introduces the reader to digital signal processing concepts, how they can be applied to sound and their use in musical effects. This makes the book suitable for a range of professionals including those working in audio engineering, as well as researchers and engineers involved in the area of digital signal processing along with students on multimedia related courses.
Emotions express a person's internal state of being and it is reflected in the speech utterances. Emotions affect the time-domain characteristics of the speech signal, namely intonation patterns, speech rate, and short-term energy function. Conventional text-to-speech (TTS) systems are built to produce speech utterances for a given text, without any emotion, which can be called as neutral speech. Building a TTS system which can produce speech utterances with expected emotion is not a trivial task, in the sense that for each of the emotions, a separate speech corpus should be carefully collected and the system should be built. Therefore, the current work focuses on incorporating happiness into neutral speech using signal processing algorithms. In this regard, neutral and happy speech are analyzed and it is found that happiness can be perceived in certain emotive words in a sentence. Thus, in order to introduce happiness into neutral speech, these emotive keywords are identified and the above mentioned time-domain parameters are modified. Linear prediction-based synthesis of happy speech is initially performed. To improve the quality of the synthesized speech, TD-PSOLA is then used. Subjective evaluation yields a mean opinion score of 2.05 (out of a maximum of 3) for happy speech synthesized using linear prediction and 2.53 for those synthesized using TD-PSOLA.
The result of the theoretical analysis of the electric field strength generated by a moving signal source is presented in this paper. The wave equation with source function taking a signal source motion into consideration is the basis of the analysis problem. To solve of the wave equation we have applied integral transformations i.e., the Laplace transform (with respect to normalized time variable) and the Fourier transform (with respect to space variables). The solution form of the analysis problem has been constructed as following: at first, we use the Cagniard-de Hoop’s method to calculate the inverse Fourier transform and next we apply inverse Laplace transform. As a numerical example, the influence of the velocity and the space location of a transmitter motion trajectory on the Doppler frequency is presented.
Contenido: Introducción; Filtros; Retardadores; Moduladores y demoduladores; Procesamiento no lineal; Efectos espaciales; Procesamiento de tiempo-segmento; Procesamiento de tiempo-frecuencia; Procesamiento del filtro fuente; Procesamiento espectral; Tiempo y frecuencia para desviar señales musicales; Control de los efectos audio digitales; Procesamiento de señal 'bitstream'.