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Optimisation of Articulated Vehicular RADAR Antenna Array Parameters Using Machine Learning Algorithms
Abstract
The ever-increasing number of RF-based advanced driver assistance systems (ADAS) applications onboard an autonomous vehicle presents with an opportunity for co-locating and sharing the RF front-ends, which in this context refers to the antenna and its associated circuitry of a RADAR. This paper proposes two sparse planar antenna array topologies synthesised for 77 GHz, by replicating a novel subarray, designed using eight isotropic antenna elements. Elements were placed manually to synthesise the novel subarray geometry, while the superarray topologies were constructed by placing subarrays of a particular orientation in a uniform superarray or by placing subarrays with fixed or optimally selected orientations in a sparse planar array, modified genetic algorithm (MGA) was employed to determine only the optimal subarray positions in the first case while the latter used it to choose both position and orientation, subject to the critical constraints dependent on the selected ADAS applications. Ultimately the comparative study of the topologies showing better performance of proposed topologies are discussed.
... For conventional radar systems, AI-based methods have been used for array selection, optimisation of beam width and direction, achieving promising results [86][87][88]. A high interest application for radar technology is RF-based driver assistance systems for autonomous driving, mainly because, in contrast to detection through optical images, radar provides images and object detection in all weather conditions, especially during low visibility circumstances [86,89]. ...
Radar systems are a topic of great interest, especially due to their extensive range of applications and ability to operate in all weather conditions. Modern radars have high requirements such as its resolution, accuracy and robustness, depending on the application. Noise Radar Technology (NRT) has the upper hand when compared to conventional radar technology in several characteristics. Its robustness to jamming, low Mutual Interference and low probability of intercept are good examples of these advantages. However, its signal processing is more complex than that associated to a conventional radar. Artificial Intelligence (AI)‐based signal processing is getting increasing attention from the research community. However, there is yet not much research on these methods for noise radar signal processing. The aim of the authors is to provide general information regarding the research performed on radar systems using AI and draw conclusions about the future of AI in noise radar. The authors introduce the use of AI‐based algorithms for NRT and provide results for its use.
... Barthelme et al. [81] studied an NN-enabled algorithm to estimate DoA with lower computational complexity. A modified genetic algorithm (GA) was implemented in another study [85] to predict the optimal position of the antenna in an RF-based advanced driving assistance system. A previous article [79] described a rotating, elevated antenna technique assisted by ML to estimate the angle for a better field of view and cost-effective automation. ...
As an integral part of the electromagnetic system, antennas are becoming more advanced and versatile than ever before, thus making it necessary to adopt new techniques to enhance their performance. Machine Learning (ML), a branch of artificial intelligence, is a method of data analysis that automates analytical model building with minimal human intervention. The potential for ML to solve unpredictable and non-linear complex challenges is attracting researchers in the field of electromagnetics (EM), especially in antenna and antenna-based systems. Numerous antenna simulations, synthesis, and pattern recognition of radiations as well as non-linear inverse scattering-based object identifications are now leveraging ML techniques. Although the accuracy of ML algorithms depends on the availability of sufficient data and expert handling of the model and hyperparameters, it is gradually becoming the desired solution when researchers are aiming for a cost-effective solution without excessive time consumption. In this context, this paper aims to present an overview of machine learning, and its applications in Electromagnetics, including communication, radar, and sensing. It extensively discusses recent research progress in the development and use of intelligent algorithms for antenna design, synthesis and analysis, electromagnetic inverse scattering, synthetic aperture radar target recognition, and fault detection systems. It also provides limitations of this emerging field of study. The unique aspect of this work is that it surveys the state-of the art and recent advances in ML techniques as applied to EM.
Joint radar and communication (JRC) technology has become important for civil and military applications for decades. This paper introduces the concepts, characteristics and advantages of JRC technology, presenting the typical applications that have benefited from JRC technology currently and in the future. This paper explores the state-of-the-art of JRC in the levels of coexistence, cooperation, co-design and collaboration. Compared to previous surveys, this paper reviews the entire trends that drive the development of radar sensing and wireless communication using JRC. Specifically, we explore an open research issue on radar and communication operating with mutual benefits based on collaboration, which represents the fourth stage of JRC evolution. This paper provides useful perspectives for future researches of JRC technology.
Sharing of the frequency bands between radar and communication systems has attracted substantial attention, as it can avoid under-utilization of otherwise permanently allocated spectral resources, thus improving efficiency. Further, there is increasing demand for radar and communication systems that share the hardware platform as well as the frequency band, as this not only decongests the spectrum, but also benefits both sensing and signaling operations via the full cooperation between both functionalities. Nevertheless, its success critically hinges on high-quality joint radar and communication designs. In the first part of this paper, we overview the research progress in the
areas of radar-communication coexistence and dual-functional radar-communication (DFRC) systems, with particular emphasis on the application scenarios and the technical approaches. In the second part, we propose a novel transceiver architecture and frame structure for a DFRC base station (BS) operating in the millimeter wave (mmWave) band, using the hybrid analog-
digital (HAD) beamforming technique. We assume that the BS is serving a multi-antenna user equipment (UE) over a mmWave channel, and at the same time it actively detects targets. The targets also play the role of scatterers for the communication signal. In that framework, we propose a novel scheme for joint target search and communication channel estimation relying on omni-directional pilot signals generated by the HAD structure. Given a fully-digital communication precoder and a desired radar transmit beampattern, we propose to design the analog and digital precoders under non-convex constant-modulus (CM) and power constraints, such that the BS can formulate narrow beams towards all the targets, while pre-equalizing the impact of the communication channel. Furthermore, we design a HAD receiver that can simultaneously process signals from the UE and echo waves from the targets. By tracking the angular variation of the targets, we show that it is possible to recover the target echoes and mitigate its potential interference imposed on the UE signals, even when the radar and communication signals share
the equivalent signal-to-noise ratio (SNR). The feasibility and the efficiency of the proposed approaches in realizing DFRC are verified via numerical simulations. Finally, our discussions are summarized by overviewing the open problems in the research field of communication and radar spectrum sharing (CRSS).
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Automotive radar is the most promising and fastest-growing civilian application of radar technology. Vehicular radars provide the key enabling technology for the autonomous driving revolution that will have a dramatic impact on everyone's day-to-day lives. They play a central role in the autonomous sensing suit because of the significant progress in the radio-frequency (RF) CMOS technology that enables high-level radaron-chip integration and thus reduces the automotive radar cost to the level of consumer mass production. However, this would not be sufficient without high spatial resolution performance, which can be obtained by multiple-input, multiple-output (MIMO) and cognitive approaches at a lower cost.
Sensors are key components for all types of autonomous vehicles because they can provide the data required to perceive the surrounding environment and therefore aid the decision-making process. This paper explains how each of these sensors work, their advantages and disadvantages and how sensor fusion techniques can be utilized to create a more optimum and efficient system for autonomous vehicles.
A frequency-reconfigurable slot-ring antenna switching between and bands is presented. The aperture of an -band slot-ring antenna can be reconfigured to a 2×2 -band slot-ring antenna array by changing the states of 16 PIN diode switches. This antenna operates at 1.76/5.71 GHz with a fractional bandwidth (FBW) of 8.6%/11.5%, in the -/ -band operating states, respectively. The measured realized gain and radiation efficiency are 0.1/4.2 dBi and 66.6%/80.7%, respectively. The antenna element spacing at 5.71 GHz is 0.36 which enables beamsteering without grating lobes. This shared-aperture antenna is scalable to a larger array with element spacing of less than half wavelength in both frequency bands.
Automotive manufacturers are currently giving much interest to in-vehicle sensors and their relevant ITS applications. The number of in-vehicle sensors is in continuously increasing because of their proved benefits represented in avoided accidents, higher driving efficiencies, and ubiquitous sensing-based services. These benefits are not limited to only the vehicle's driver, but also to other vehicles and third parties. In this paper, we introduce Vehicle as a Mobile Sensor (VaaMS), a concept that shows how sensor-equipped vehicles can be considered a pivotal, mobile resource of sensory data and sensor-related applications/services. In addition, we present a new categorization of in-vehicle sensors along with a discussion of some representative sensors and several supported ITS applications. Besides, we elaborate on some communication technologies that support VaaMS.
One of significant improvement for particle swarm optimization (PSO) is through the implementation of metaheuristics hybridization that combines different metaheuristics paradigms. By using metaheuristics hybridization, the weaknesses of one algorithm can be compensated by the strengths of other algorithms. Therefore, researchers have given a lot of interest in hybridizing PSO with mutation concept from genetic algorithm (GA). The reason for incorporating mutation into PSO is to resolve premature convergence problem due to some kind of stagnation by PSO particles. Although PSO is capable to produce fast results, particles stagnation has led the algorithm to suffer from low-optimization precision. Thus, this paper introduces time-varying mutation techniques for resolving the PSO problem. The different time-varying techniques have been tested on some benchmark functions. Results from the empirical experiments have shown that most of the time-varying mutation techniques have significantly improved PSO performances not just to the results accuracy but also to the convergence time.
Digital beamforming with array antennas is often applied at subarray outputs. These subarrays can be considered as new array elements; their phase centre is separated by more than half a wavelength. This leads to grating effects when the beam is scanned digitally. We present a mathematical description and properties of digital beamforming and solutions to the grating problem obtained from different optimisation problems. The efficiency of this digital processing is sensitive against the underlying subarray configuration. From this sensitivity it can be derived that partially overlapping subarrays are better suited to reduce grating lobes than non-overlapping (single layer) subarrays or fully overlapping (double layer) subarrays
In this paper, a millimeter wave dual-polarized antenna with different radiation patterns is proposed. The antenna consists of a planar lens, a rectangular horn antenna and a quasi-planar orthomode transducer (OMT) which provides two polarizations. The quasi-planar OMT with good isolation is based on substrate integrated waveguide (SIW) technology, and it can be co-planar integrated with other millimeter wave planar circuits seamlessly. A planar lens is designed on a quad-layered substrate and it has the priority of polarization selective that only takes effect on the horizontal polarization. Consequently, high-gain with narrow-beam in horizontal polarization and low-gain with wide-beam in vertical polarization are achieved. To verify the idea, the proposed antenna is designed, fabricated and measured, achieving a high gain of 26.4dBi in horizontal polarization, and a wide beamwidth in vertical polarization. This kind of antennas can be applied to make a balance between the range and coverage in communication and radar applications. Besides, the proposed quasi-planar OMT has potential applications in fifth generation (5G) millimeter wave wireless communications. IEEE
A wideband frequency diversity printed-Yagi antenna array is presented. The operating band of the single port L-/S-bands antenna element can be selected by changing the states of p-i-n diode switches. The L- and S-bands work independently. A
S-band array can be constituted to a
L-band array by modifying the element apertures. This array operates at 1–2 GHz/2–4 GHz in the L-/S-bands with a fractional bandwidth of 66.7%/66.7%, which is translated into an overall tuning ratio of 4:1. The spacing of adjacent antenna elements at each reconfigurable mode is less than
(
represents the free-space wavelength of the highest frequency in the operating band), which achieves no grating lobes in the radiation field. The proposed antenna array is simulated, fabricated, and tested with reasonable agreement between measurements and simulations. In this way, a rudiment of wider tuning ratio array is designed for wideband reconnaissance applications.
In this communication, a novel substrate integrated waveguide (SIW) slot array with flat-shoulder shaped radiation pattern is introduced for both 77GHz automotive Medium Range Radar (MRR) and Long Range Radar (LRR) applications. The operational principle of the antenna is introduced, while the synthesis of the desired radiation pattern is facilitated by a mixed optimization method, including non-linear fitting and Aggressive Space Mapping (ASM). Experiments are carried out and the measured peak gain of the proposed array is 21.7dBi. The demonstrated antenna presents to be an excellent candidate for 77GHz automotive radar application. IEEE
This book constitutes the thoroughly refereed post-conference proceedings of the third International Symposium on Intelligent Systems Technologies and Applications (ISTA’17), September 13-16, 2017, Manipal, Karnataka, India. All submissions were evaluated on the basis of their significance, novelty, and technical quality. This proceedings contains 34 papers selected for presentation at the Symposium.
A novel array antenna with a flat-shoulder shaped radiation pattern is proposed as the transmitting antenna for 77GHz automotive radar application. When it is used in an automotive radar comprising one transmitter and multiple identical receivers, it can meet the demands of both long range and medium range detection without switching the operation mode back and forth between the long range radar (LRR) scenario and the medium range radar (MRR) scenario. The proposed antenna concept is fully introduced to explain its mechanism. An unconventional array was synthesized to achieve the desired flat-shoulder shaped radiation pattern. Prototype of the proposed array antenna was also designed according to the array synthesis result, which consists of several linear series-fed patch arrays and a substrate integrated waveguide (SIW) power and phase distributing network. Fabrication and measurement of the prototype array antenna were completed, showing a good agreement between the measured data and the synthesized as well as the simulated results, thereby validating the design.
Traffic has become more complex in recent years and therefore the expectations that are placed on automobiles have also risen sharply. Support for drivers and the protection of the occupants of vehicles and other persons involved in road traffic have become essential. Rapid technical developments and innovative advances in recent years have enabled the development of plenty of Advanced Driver Assistance Systems that are based on different working principles such as radar, lidar or camera techniques. Some systems only warn the drivers via a visual, audible or haptical signal of a danger. Other systems are used to actively engage in the control of a vehicle in emergency situations. Although technical development is already quite mature, there are still many development opportunities for improving road safety. The further development of current applications and the creation of new applications that are based on sensor fusion are essential for the future. A short summary of capabilities of ADAS systems and selected ADAS modules was presented in this paper. The review was selected toward the future perspective of sensors fusion applied on the autonomous mobile platform.
Synthetic aperture Radar (SAR) has been extensively used for space-borne Earth observations in recent times. In conventional SAR systems analog beam-steering techniques are capable of implementing multiple operational modes, such as the Stripmap, ScanSAR, and Spotlight, to fulfill the different requirements in terms of spatial resolution and coverage. Future RADAR satellites need to resolve the complex issues such as wide area coverage and resolution. Digital beam-forming (DBF) is a promising technique to overcome the problems mentioned above. In communication satellites DBF technique is already implemented. This paper discuses the relevance of DBF in space-borne RADAR satellites for enhancements to quality imaging. To implement DBF in SAR, processing of SAR data is an important step. This work focused on processing of Level 1.1 and 1.5 SAR image data. The SAR raw data is computationally intensive to process. To resolve the computation problem, high performance computing (HPC) is necessary. The relevance of HPC for SAR data processing using an off-the-shelf graphical processing unit (GPU) over CPU is discussed in this paper. Quantitative estimates on SAR image processing performance comparisons using both CPU and GPU are also provided as validation for the results.
A concept for reconfigurable L/S band phased arrays with a frequency switchable antenna element is presented. It is demonstrated with full-wave simulations that the proposed array structure is suitable for a wide angle scan in both frequency bands.
In array design, the positions of sparse array elements is an important concern for optimal performance in terms of its ability to achieve minimum peak sidelobe level (SLL). This paper proposes a modified real genetic algorithm (MGA) based on resetting of chromosome for the element position optimization of sparse planar arrays with rectangular boundary. And here the multiple optimization constraints include the number of elements, the aperture and the minimum element spacing. By simplifying the space between the elements from the actual distance to Chebychev distance, the MGA searches a smaller solution space by means of indirect description of individual, and it can avoid infeasible solution during the optimization process by two novel genetic operators. Finally, the simulation results confirming the great efficiency and the robustness of the proposed method are shown in this paper
Various techniques for optimizing the performance indices of antenna arrays are discussed. In particular, methods for maximizing array directivity and signal-to-noise power ratio are reviewed. These performance indices are expressible as a ratio of two Hermitian forms, which has a certain special property to enable the facile determination of both its maximum value and the conditions under which this maximum is attained. Special maximization procedures by excitation amplitude and phase adjustments, by spacing perturbation, by phase adjustments only, and by a coordinate transformation with constraints on the array pattern are examined. For wire antennas the method of moments using a subsectioning technique can be applied to obtain numerical answers which include mutual-coupling effects. Methods for considering large arrays and for the maximization of power gain are indicated.
Compact multi-beam dual-frequency (24 and 77 GHz) imaging antenna for automotive radars
- R Schoenlinner
- J P Ebling
- L C Kempel
- G M Rebeiz
PAM4-based RADAR counter-measures in hostile environments
- S Srivatsa
- S G A Sundaram