Pub Date : 2020-09-21DOI: 10.1109/RadarConf2043947.2020.9266357
B. Ng, L. Rosenberg
Coherent detection schemes have been shown to offer performance benefits over non-coherent techniques in the maritime radar context. To further improve performance, the use of sparse representations with judiciously selected dictionaries has been proposed as a method to separate target returns from surrounding sea clutter. This paper exploits a robust frequency estimation scheme to effectively separate the target from clutter and noise. The approach offers two advantages: (1) it does not require a dictionary to be designed to support the scheme and (2) the scheme is capable of estimating multiple frequencies, thus suitable for targets with multiple Doppler components. In this work, we use both real and simulated sea clutter with synthetic targets for evaluation. It is found that the proposed technique can improve performance over traditional coherent detection for both point targets and more complex targets with multiple frequency components.
{"title":"Maritime Target Detection using Frequency Estimation","authors":"B. Ng, L. Rosenberg","doi":"10.1109/RadarConf2043947.2020.9266357","DOIUrl":"https://doi.org/10.1109/RadarConf2043947.2020.9266357","url":null,"abstract":"Coherent detection schemes have been shown to offer performance benefits over non-coherent techniques in the maritime radar context. To further improve performance, the use of sparse representations with judiciously selected dictionaries has been proposed as a method to separate target returns from surrounding sea clutter. This paper exploits a robust frequency estimation scheme to effectively separate the target from clutter and noise. The approach offers two advantages: (1) it does not require a dictionary to be designed to support the scheme and (2) the scheme is capable of estimating multiple frequencies, thus suitable for targets with multiple Doppler components. In this work, we use both real and simulated sea clutter with synthetic targets for evaluation. It is found that the proposed technique can improve performance over traditional coherent detection for both point targets and more complex targets with multiple frequency components.","PeriodicalId":161046,"journal":{"name":"2020 IEEE Radar Conference (RadarConf20)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121816399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-21DOI: 10.1109/RadarConf2043947.2020.9266669
Liangliang Wang, Gongjian Zhou, T. Kirubarajan
Traditional dynamic programming based track-before-detect (DP- TBD) methods may suffer performance loss due to the suboptimal preprocessing. In this paper, a DP-TBD method based on preprocessing with pseudo-spectrum is proposed. For each cell in the observed image, a pseudo-spectrum is constructed around the cell itself with measurement value as its peak according to a point spread function. Samples of the pseudo-spectrum are added onto corresponding cells in the current frame. This facilitates improved performance through the intraframe integration by using spilled target echo energy. Then, dynamic programming procedure is performed for mul-tiframe integration. The pseudo-spectrum based preprocessing is presented, and energy integration procedure for the proposed DP- TBD is provided in detail. Theoretical analysis and simulation result demonstrate the validity of the proposed method.
{"title":"Track-Before-Detect Method Based on Preprocessing with Pseudo-Spectrum","authors":"Liangliang Wang, Gongjian Zhou, T. Kirubarajan","doi":"10.1109/RadarConf2043947.2020.9266669","DOIUrl":"https://doi.org/10.1109/RadarConf2043947.2020.9266669","url":null,"abstract":"Traditional dynamic programming based track-before-detect (DP- TBD) methods may suffer performance loss due to the suboptimal preprocessing. In this paper, a DP-TBD method based on preprocessing with pseudo-spectrum is proposed. For each cell in the observed image, a pseudo-spectrum is constructed around the cell itself with measurement value as its peak according to a point spread function. Samples of the pseudo-spectrum are added onto corresponding cells in the current frame. This facilitates improved performance through the intraframe integration by using spilled target echo energy. Then, dynamic programming procedure is performed for mul-tiframe integration. The pseudo-spectrum based preprocessing is presented, and energy integration procedure for the proposed DP- TBD is provided in detail. Theoretical analysis and simulation result demonstrate the validity of the proposed method.","PeriodicalId":161046,"journal":{"name":"2020 IEEE Radar Conference (RadarConf20)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115815804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-21DOI: 10.1109/RadarConf2043947.2020.9266342
John Markow, A. Balleri
Radars monitoring small targets often must increase their integration times to achieve sufficient signal-to-noise ratio (SNR) for maintaining a viable track. These longer integation times can prevent micro-Doppler signature extraction and instead result in Doppler signatures consisting of spectral lines to the radar's higher-level processing. Whether the radar operates in the micro-Doppler or spectral line regime depends on both radar parameters (e.g. waveforms, wavelengths and integration times) as well as target parameters (e.g. rotor length, rotational frequency, target reflectivity and geometry). Additionally, understanding the transition region between these regimes can further aid target recognition algorithms. This paper uses modelling, simulations and experimental data to refine the understanding of how a particular radar will observe a target Doppler signature in either of these regimes, highlighting the transition region between the two.
{"title":"Examination of Drone Micro-Doppler and JEM/HERM Signatures","authors":"John Markow, A. Balleri","doi":"10.1109/RadarConf2043947.2020.9266342","DOIUrl":"https://doi.org/10.1109/RadarConf2043947.2020.9266342","url":null,"abstract":"Radars monitoring small targets often must increase their integration times to achieve sufficient signal-to-noise ratio (SNR) for maintaining a viable track. These longer integation times can prevent micro-Doppler signature extraction and instead result in Doppler signatures consisting of spectral lines to the radar's higher-level processing. Whether the radar operates in the micro-Doppler or spectral line regime depends on both radar parameters (e.g. waveforms, wavelengths and integration times) as well as target parameters (e.g. rotor length, rotational frequency, target reflectivity and geometry). Additionally, understanding the transition region between these regimes can further aid target recognition algorithms. This paper uses modelling, simulations and experimental data to refine the understanding of how a particular radar will observe a target Doppler signature in either of these regimes, highlighting the transition region between the two.","PeriodicalId":161046,"journal":{"name":"2020 IEEE Radar Conference (RadarConf20)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116678138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-21DOI: 10.1109/RadarConf2043947.2020.9266510
Kheireddine Aziz, E. De Greef, M. Rykunov, A. Bourdoux, H. Sahli
This paper presents a radar and camera sensor fusion framework as a vulnerable road user (VRU) perception system that can automatically detect, track and classify different targets on the road. The first module of the system performs a spatial-temporal alignment on a common plane of detections provided by the radar signal processing and video processing modules. The second module is dedicated to data association of the aligned detections. A centralized fusion algorithm takes the current aligned detection set (locations and labels) as inputs from both sensors and performs multi-object tracking with a joint probabilistic data association (JPDAF) algorithm underlying the Kalman filter. The proposed radar/camera fusion system is experimentally evaluated through multi-object tracking scenarios. The experimental results demonstrate its reliability and effectiveness compared to a single sensor system
{"title":"Radar-camera Fusion for Road Target Classification","authors":"Kheireddine Aziz, E. De Greef, M. Rykunov, A. Bourdoux, H. Sahli","doi":"10.1109/RadarConf2043947.2020.9266510","DOIUrl":"https://doi.org/10.1109/RadarConf2043947.2020.9266510","url":null,"abstract":"This paper presents a radar and camera sensor fusion framework as a vulnerable road user (VRU) perception system that can automatically detect, track and classify different targets on the road. The first module of the system performs a spatial-temporal alignment on a common plane of detections provided by the radar signal processing and video processing modules. The second module is dedicated to data association of the aligned detections. A centralized fusion algorithm takes the current aligned detection set (locations and labels) as inputs from both sensors and performs multi-object tracking with a joint probabilistic data association (JPDAF) algorithm underlying the Kalman filter. The proposed radar/camera fusion system is experimentally evaluated through multi-object tracking scenarios. The experimental results demonstrate its reliability and effectiveness compared to a single sensor system","PeriodicalId":161046,"journal":{"name":"2020 IEEE Radar Conference (RadarConf20)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127100377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-21DOI: 10.1109/RadarConf2043947.2020.9266331
Tao Fan, Mengmeng Ge, Na Gan, Yanqin Xu, G. Cui, Zhihao Jiang
This paper deals with the joint design of transmit waveform and receive filter to improve the clutter rejection capability for non-uniform pulse repetition interval (NUPRI) airborne radar. Specifically, a multipulse echo model accounting for a moving point-like target and signal-dependent clutter is first established. Then the echo is processed via the matching filter and the windowed Doppler filter bank to obtain the two-dimensional range-Doppler plane. Further, the integrated sidelobe level of clutter (ISLC) that spreads the region of the target of interest in the plane is considered to minimize forcing constant modulus constraint on the waveform. To solve the resultant nonconvex problem, the Sequential Greedy Optimization Algorithm (SGOA) through alternately updating the receive filter and transmit waveform is proposed to monotonically decrease ISLC to converge. In each iteration, the iterative algorithm based on coordinate descent (CD) framework and the sequential convex approximation algorithm are, respectively, explored to obtain the transmit waveform and receive filter. Finally, the performance of the proposed algorithm is assessed through numerical simulations showing its capability to suppress signal-dependent clutter.
{"title":"Transmit-Receive Design for Non-Uniform Pulse Repetition Interval Airborne Radar in the Presence of Signal-Dependent Clutter","authors":"Tao Fan, Mengmeng Ge, Na Gan, Yanqin Xu, G. Cui, Zhihao Jiang","doi":"10.1109/RadarConf2043947.2020.9266331","DOIUrl":"https://doi.org/10.1109/RadarConf2043947.2020.9266331","url":null,"abstract":"This paper deals with the joint design of transmit waveform and receive filter to improve the clutter rejection capability for non-uniform pulse repetition interval (NUPRI) airborne radar. Specifically, a multipulse echo model accounting for a moving point-like target and signal-dependent clutter is first established. Then the echo is processed via the matching filter and the windowed Doppler filter bank to obtain the two-dimensional range-Doppler plane. Further, the integrated sidelobe level of clutter (ISLC) that spreads the region of the target of interest in the plane is considered to minimize forcing constant modulus constraint on the waveform. To solve the resultant nonconvex problem, the Sequential Greedy Optimization Algorithm (SGOA) through alternately updating the receive filter and transmit waveform is proposed to monotonically decrease ISLC to converge. In each iteration, the iterative algorithm based on coordinate descent (CD) framework and the sequential convex approximation algorithm are, respectively, explored to obtain the transmit waveform and receive filter. Finally, the performance of the proposed algorithm is assessed through numerical simulations showing its capability to suppress signal-dependent clutter.","PeriodicalId":161046,"journal":{"name":"2020 IEEE Radar Conference (RadarConf20)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127216761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-21DOI: 10.1109/RadarConf2043947.2020.9266588
A. Babu, S. Baumgartner
Since the road infrastructure is an important factor for the economy and safety, the continuous monitoring of the road condition is a necessity. Compared to the widely used costly, time consuming and labour-intensive road condition monitoring using measurement vehicles all over the country, the potential of SAR polarimetry to remotely monitor the road surface roughness, cracks and potholes are investigated in this study. The polarimetric analysis of fully polarimetric X-band radar datasets acquired over the Kaufbeuren test site with DLR's airborne sensor F-SAR revealed that the anisotropy and coherency matrix (T3) elements are sensitive to the road surface roughness and can be used to retrieve the vertical surface roughness. The cross-polar sigma nought images show a considerable increase in their magnitude over the cracks and potholes on the road surface. The initial experimental results obtained from this study are discussed in this paper.
{"title":"Road Surface Quality Assessment Using Polarimetric Airborne SAR","authors":"A. Babu, S. Baumgartner","doi":"10.1109/RadarConf2043947.2020.9266588","DOIUrl":"https://doi.org/10.1109/RadarConf2043947.2020.9266588","url":null,"abstract":"Since the road infrastructure is an important factor for the economy and safety, the continuous monitoring of the road condition is a necessity. Compared to the widely used costly, time consuming and labour-intensive road condition monitoring using measurement vehicles all over the country, the potential of SAR polarimetry to remotely monitor the road surface roughness, cracks and potholes are investigated in this study. The polarimetric analysis of fully polarimetric X-band radar datasets acquired over the Kaufbeuren test site with DLR's airborne sensor F-SAR revealed that the anisotropy and coherency matrix (T3) elements are sensitive to the road surface roughness and can be used to retrieve the vertical surface roughness. The cross-polar sigma nought images show a considerable increase in their magnitude over the cracks and potholes on the road surface. The initial experimental results obtained from this study are discussed in this paper.","PeriodicalId":161046,"journal":{"name":"2020 IEEE Radar Conference (RadarConf20)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125877124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-21DOI: 10.1109/RadarConf2043947.2020.9266404
Gabriel Beltr˜ao, M. Alaee-Kerahroodi, Udo Schroeder, Bhavani Shankar
This paper presents the joint design of discrete slow-time radar waveform and receive filter, with the aim of enhancing the Signal to Interference and Noise Ratio (SINR) in phase coded radar systems for vital-sign monitoring. Towards this, we consider maximizing the SINR at the input of the vital-sign estimation block, when transmitting hardware efficient Mary Phase Shift Keying (MPSK) sequences. This multi-variable and non-convex optimization problem is efficiently solved based on a Minimum Variance Distortionless Response (MVDR) filter, with the Coordinate Descent (CD) approach for the sequence optimization, and the obtained results have shown attractive interference suppression capabilities, even for the simple binary case.
{"title":"Joint Waveform/Receiver Design for Vital-Sign Detection in Signal-Dependent Interference","authors":"Gabriel Beltr˜ao, M. Alaee-Kerahroodi, Udo Schroeder, Bhavani Shankar","doi":"10.1109/RadarConf2043947.2020.9266404","DOIUrl":"https://doi.org/10.1109/RadarConf2043947.2020.9266404","url":null,"abstract":"This paper presents the joint design of discrete slow-time radar waveform and receive filter, with the aim of enhancing the Signal to Interference and Noise Ratio (SINR) in phase coded radar systems for vital-sign monitoring. Towards this, we consider maximizing the SINR at the input of the vital-sign estimation block, when transmitting hardware efficient Mary Phase Shift Keying (MPSK) sequences. This multi-variable and non-convex optimization problem is efficiently solved based on a Minimum Variance Distortionless Response (MVDR) filter, with the Coordinate Descent (CD) approach for the sequence optimization, and the obtained results have shown attractive interference suppression capabilities, even for the simple binary case.","PeriodicalId":161046,"journal":{"name":"2020 IEEE Radar Conference (RadarConf20)","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123314870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-21DOI: 10.1109/RadarConf2043947.2020.9266429
L. Sadaoui, J. Lantéri, J. Dauvignac, C. Migliaccio, F. Ferrero, L. Brochier, Ronnie Rexhaeuser, T. Lenhard, Federico Lolli, Claudio Palleschi
The paper presents a design of a SIW (Substrate Integrated Waveguide) slot's antenna in W band for a sense-and-avoid radar module to tackle an emerging need of security during landing and take-off for small aircrafts. This work is developed inside the ODESSA project, funded by the European Union. The antenna was formed by 7 slots etched on the top face of a SIW structure designed on a Rogers RO3003G2 substrate. Simulation and experimental results, for both cases with and without radome, are presented inside 76–80 GHz frequency range. Good performances are obtained for efficiency and realized gain which were the main objectives of this work.
{"title":"Design of a Substrate Integrated Waveguide Slots Antenna in W Band for Aircraft Radar Application","authors":"L. Sadaoui, J. Lantéri, J. Dauvignac, C. Migliaccio, F. Ferrero, L. Brochier, Ronnie Rexhaeuser, T. Lenhard, Federico Lolli, Claudio Palleschi","doi":"10.1109/RadarConf2043947.2020.9266429","DOIUrl":"https://doi.org/10.1109/RadarConf2043947.2020.9266429","url":null,"abstract":"The paper presents a design of a SIW (Substrate Integrated Waveguide) slot's antenna in W band for a sense-and-avoid radar module to tackle an emerging need of security during landing and take-off for small aircrafts. This work is developed inside the ODESSA project, funded by the European Union. The antenna was formed by 7 slots etched on the top face of a SIW structure designed on a Rogers RO3003G2 substrate. Simulation and experimental results, for both cases with and without radome, are presented inside 76–80 GHz frequency range. Good performances are obtained for efficiency and realized gain which were the main objectives of this work.","PeriodicalId":161046,"journal":{"name":"2020 IEEE Radar Conference (RadarConf20)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125570297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-21DOI: 10.1109/RadarConf2043947.2020.9266415
Penghui Zhang, Kezhu Liu, Wujun Li, Wei Yi, Xiaobo Yang
The positioning ability of the DOA estimation algorithms in array signal processing depends on the correct selection of snapshot data including the target echo signal. However, in the scene with low signal-to-noise ratio (SNR), the CFAR method, which is frequently used before DOA estimation, cannot effectively discover the snapshot data containing the targets, resulting in the loss of the target. In this paper, we propose a multi-frame DOA (MF-DOA) estimation algorithm, which implements multi-frame energy accumulation and snapshot data extraction based on the introduced target motion model so that the weak moving targets can be effectively located. The simulation data and real MIMO radar data are processed, and the results show that the MF-DOA algorithm has good ability to excavate weak moving targets and extend the radar detection range.
{"title":"Multi-frame DOA Estimation Algorithm for Weak Moving Targets","authors":"Penghui Zhang, Kezhu Liu, Wujun Li, Wei Yi, Xiaobo Yang","doi":"10.1109/RadarConf2043947.2020.9266415","DOIUrl":"https://doi.org/10.1109/RadarConf2043947.2020.9266415","url":null,"abstract":"The positioning ability of the DOA estimation algorithms in array signal processing depends on the correct selection of snapshot data including the target echo signal. However, in the scene with low signal-to-noise ratio (SNR), the CFAR method, which is frequently used before DOA estimation, cannot effectively discover the snapshot data containing the targets, resulting in the loss of the target. In this paper, we propose a multi-frame DOA (MF-DOA) estimation algorithm, which implements multi-frame energy accumulation and snapshot data extraction based on the introduced target motion model so that the weak moving targets can be effectively located. The simulation data and real MIMO radar data are processed, and the results show that the MF-DOA algorithm has good ability to excavate weak moving targets and extend the radar detection range.","PeriodicalId":161046,"journal":{"name":"2020 IEEE Radar Conference (RadarConf20)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126768512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-21DOI: 10.1109/RadarConf2043947.2020.9266540
Canan Aydogdu, H. Wymeersch, Mats Rydström
Radar communications (RadCom) is a spectrally efficient way for removing automotive radar interference and thereby enhancing reliable radar sensing, via a single hardware for both radar and communications. When interference coordination does not use all the RadCom resources, opportunities for communicating additional data arise. We propose a new communication protocol, termed RadNet (for radar network), which forms a vehicular ad-hoc multi-hop network by automotive radars in a distributed manner. Simulation results obtained for high-way use cases show that RadNet can enable several Mbps data links without degrading the radar performance.
{"title":"Can Automotive Radars Form Vehicular Networks?","authors":"Canan Aydogdu, H. Wymeersch, Mats Rydström","doi":"10.1109/RadarConf2043947.2020.9266540","DOIUrl":"https://doi.org/10.1109/RadarConf2043947.2020.9266540","url":null,"abstract":"Radar communications (RadCom) is a spectrally efficient way for removing automotive radar interference and thereby enhancing reliable radar sensing, via a single hardware for both radar and communications. When interference coordination does not use all the RadCom resources, opportunities for communicating additional data arise. We propose a new communication protocol, termed RadNet (for radar network), which forms a vehicular ad-hoc multi-hop network by automotive radars in a distributed manner. Simulation results obtained for high-way use cases show that RadNet can enable several Mbps data links without degrading the radar performance.","PeriodicalId":161046,"journal":{"name":"2020 IEEE Radar Conference (RadarConf20)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114895681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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