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F. Uysal
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30 records found
1
A wide-swath synthetic aperture radar (SAR) image is known to be achievable by merging multistatic aliased data that is collected with an appropriate along track displacement. However, in terms of both flexibility requirements like potentiality of both along track and cross track interferometry and design requirements like orbital safety etc., a cross track baseline is not only demanded but also unavoidable. In this work, two methods are proposed in order to merge SAR data to recover the Doppler spectrum unambiguously for the non zero cross track baseline case. The algorithms are compared and validated by simulating an azimuth invariant multistatic SAR satellite constellation. The results are promising in terms of dealing with long cross track baselines.
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A wide-swath synthetic aperture radar (SAR) image is known to be achievable by merging multistatic aliased data that is collected with an appropriate along track displacement. However, in terms of both flexibility requirements like potentiality of both along track and cross track interferometry and design requirements like orbital safety etc., a cross track baseline is not only demanded but also unavoidable. In this work, two methods are proposed in order to merge SAR data to recover the Doppler spectrum unambiguously for the non zero cross track baseline case. The algorithms are compared and validated by simulating an azimuth invariant multistatic SAR satellite constellation. The results are promising in terms of dealing with long cross track baselines.
Conference paper
(2021)
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Niels J. de Jong, Matern P.G. Otten, Miguel Caro Cuenca, Faruk Uysal, Jacco J.M. de Wit
This paper investigates the benefits of multichannel processing for inverse synthetic aperture radar (ISAR) imaging. There are potential advantages of multichannel processing in radar systems, for example, improved motion estimation, clutter suppression, extraction of supporting information, such as sea wave direction and speed, and ship wake imaging. The current study focuses on two multichannel techniques, namely the oceanic displaced phase centre antenna (ODPCA) and the minimum variance distortionless response (MVDR) techniques, to suppress (ambiguous) clutter and enhance focused target responses even in the proximity of other target responses. These techniques are validated using experimental multichannel radar data from an airborne measurement campaign in a maritime environment.
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This paper investigates the benefits of multichannel processing for inverse synthetic aperture radar (ISAR) imaging. There are potential advantages of multichannel processing in radar systems, for example, improved motion estimation, clutter suppression, extraction of supporting information, such as sea wave direction and speed, and ship wake imaging. The current study focuses on two multichannel techniques, namely the oceanic displaced phase centre antenna (ODPCA) and the minimum variance distortionless response (MVDR) techniques, to suppress (ambiguous) clutter and enhance focused target responses even in the proximity of other target responses. These techniques are validated using experimental multichannel radar data from an airborne measurement campaign in a maritime environment.
The paper analyses the performances of a system concept consisting in a swarm of satellites operating in the SIMO (Single Input Multiple Output) configuration. In particular, two different data collection approaches, using constant and pseudo-random PRF, are analysed and compared for different number of satellites and various baseline knowledge uncertainties. In addition to the methods in literature, we propose a PRF optimisation algorithm based on the PSD (Power Spectral Density) of the received signal.These approaches are applied to the bi-dimensional case with a 2D simulator based on the chirp scaling algorithm used to synthesize jointly focused SAR images.
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The paper analyses the performances of a system concept consisting in a swarm of satellites operating in the SIMO (Single Input Multiple Output) configuration. In particular, two different data collection approaches, using constant and pseudo-random PRF, are analysed and compared for different number of satellites and various baseline knowledge uncertainties. In addition to the methods in literature, we propose a PRF optimisation algorithm based on the PSD (Power Spectral Density) of the received signal.These approaches are applied to the bi-dimensional case with a 2D simulator based on the chirp scaling algorithm used to synthesize jointly focused SAR images.
Conference paper
(2021)
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Keith T.J. Klein, Faruk Uysal, Miguel Caro Cuenca, Matern P.G. Otten, Jacco J.M. de Wit
Continuous navigation is crucial for small drones when flying a pre-planned route or during autonomous flight. In scenarios where a global positioning system (GPS) signal is unavailable, drift in the onboard sensors causes the inertial navigation system (INS) to quickly deviate from the planned route. This paper proposes a radar-aided navigation method for small drones which is able to estimate the horizontal velocity and height of the platform independently from GPS. The method is based on an omnidirectional radar system and takes advantage of multi-look processing to increase estimation precision. Simulations and experiments verify that an omnidirectional radar can be used to successfully estimate the velocity and course of a small drone platform.
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Continuous navigation is crucial for small drones when flying a pre-planned route or during autonomous flight. In scenarios where a global positioning system (GPS) signal is unavailable, drift in the onboard sensors causes the inertial navigation system (INS) to quickly deviate from the planned route. This paper proposes a radar-aided navigation method for small drones which is able to estimate the horizontal velocity and height of the platform independently from GPS. The method is based on an omnidirectional radar system and takes advantage of multi-look processing to increase estimation precision. Simulations and experiments verify that an omnidirectional radar can be used to successfully estimate the velocity and course of a small drone platform.
Journal article
(2021)
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Richard J. de Jong, Jacco J.M. de Wit, Faruk Uysal
In the defence and security domain, camera systems are widely used for surveillance. The major advantage of using camera systems for surveillance is that they provide high‐resolution imagery, which is easy to interpret. However, the use of camera systems and optical imagery has some drawbacks, especially for application in the military domain. In poor lighting conditions, dust or smoke the image quality degrades and, additionally, cameras cannot provide range information too. These drawbacks can be mitigated by exploiting the strengths of radar. Radar performance can be largely maintained during the night, in various weather conditions and in dust and smoke. Moreover, radar provides the distance to detected objects. Since, the strongpoints and weaknesses of radar and camera systems seem complementary, a natural question is: can radar and camera systems learn from each other? Here the potential of radar/video multimodal learning is evaluated for human activity classification. The novelty of this work is the use of radar spectrograms and related video frames for classification with a multimodal neural network. Radar spectrograms and video frames are both two‐dimensional images, but the information they contain is of different nature. This approach was adopted to limit the required preprocessing load, while maintaining the complementary nature of the sensor data.
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In the defence and security domain, camera systems are widely used for surveillance. The major advantage of using camera systems for surveillance is that they provide high‐resolution imagery, which is easy to interpret. However, the use of camera systems and optical imagery has some drawbacks, especially for application in the military domain. In poor lighting conditions, dust or smoke the image quality degrades and, additionally, cameras cannot provide range information too. These drawbacks can be mitigated by exploiting the strengths of radar. Radar performance can be largely maintained during the night, in various weather conditions and in dust and smoke. Moreover, radar provides the distance to detected objects. Since, the strongpoints and weaknesses of radar and camera systems seem complementary, a natural question is: can radar and camera systems learn from each other? Here the potential of radar/video multimodal learning is evaluated for human activity classification. The novelty of this work is the use of radar spectrograms and related video frames for classification with a multimodal neural network. Radar spectrograms and video frames are both two‐dimensional images, but the information they contain is of different nature. This approach was adopted to limit the required preprocessing load, while maintaining the complementary nature of the sensor data.
Conference paper
(2021)
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Keith T.J. Klein, Faruk Uysal, Miguel Caro Cuenca, Matern P.G. Otten, Jacco J.M. De Wit
Synthetic aperture radar (SAR) processing on agile radar platforms requires a very accurate estimate of position due to the unpredictable trajectory of such platforms. This is even more challenging in GPS-denied scenarios where the bias in inertial sensors cannot be compensated. In this study, we propose a 3D radar-Aided positioning method based on SAR autofocusing to achieve subresolution positioning accuracy. The proposed multibeam autofocus algorithm builds on multiple SAR motion compensation techniques to generalize and provide a framework for simultaneous omnidirectional imaging and trajectory estimation and correction while taking advantage of the beamforming capabilities of the antenna array. Our initial simulations and proof of concept show that the performance of the proposed approach is adequate even in low signal-To-noise ratio cases.
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Synthetic aperture radar (SAR) processing on agile radar platforms requires a very accurate estimate of position due to the unpredictable trajectory of such platforms. This is even more challenging in GPS-denied scenarios where the bias in inertial sensors cannot be compensated. In this study, we propose a 3D radar-Aided positioning method based on SAR autofocusing to achieve subresolution positioning accuracy. The proposed multibeam autofocus algorithm builds on multiple SAR motion compensation techniques to generalize and provide a framework for simultaneous omnidirectional imaging and trajectory estimation and correction while taking advantage of the beamforming capabilities of the antenna array. Our initial simulations and proof of concept show that the performance of the proposed approach is adequate even in low signal-To-noise ratio cases.
Mutual interference between different radar waveforms used in automotive radar applications is studied. The existing interference analysis is extended to a generalised radar-to-radar interference equation that covers most of the common interference scenarios for automotive radar systems. The outcome of the generalised equation is demonstrated for a number of typical scenarios where radars with different continuously transmitting waveforms are involved. The proposed equation can be used to characterise the received interference and its features by analysing the instantaneous beat frequency of the victim radar. Moreover, an interference analysis of phase-coded frequency-modulated continuous waveforms is performed and demonstrated experimentally by using real-time automotive radars for the first time in the literature. The experimental results corroborate the interference analysis of different waveforms and validate the proposed generalised interference equation under various conditions.
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Mutual interference between different radar waveforms used in automotive radar applications is studied. The existing interference analysis is extended to a generalised radar-to-radar interference equation that covers most of the common interference scenarios for automotive radar systems. The outcome of the generalised equation is demonstrated for a number of typical scenarios where radars with different continuously transmitting waveforms are involved. The proposed equation can be used to characterise the received interference and its features by analysing the instantaneous beat frequency of the victim radar. Moreover, an interference analysis of phase-coded frequency-modulated continuous waveforms is performed and demonstrated experimentally by using real-time automotive radars for the first time in the literature. The experimental results corroborate the interference analysis of different waveforms and validate the proposed generalised interference equation under various conditions.
Conference paper
(2020)
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R. van Gaalen, Faruk Uysal
This paper establishes novel methods for vehicle localization and mapping using a 1D linear automotive radar array in conjuncture with pre-existing lidar maps, and tests if the generated radar map can be made to be 3 dimensional. The basic design of this study was to implement a SLAM (Simultaneous Localization And Mapping) system that co-registers radar data to radar data, and/or register radar data to lidar data. After the execution of experiments, it was established that it is possible to localize the car by relating observed radar data to premade lidar maps, and to continually add to a cumulative map made with the radar data that can further aid the localization process. Furthermore, the radar map created using the 1D linear automotive array can be extended to 3D with proposed processing chain, though more experiments to establish the full potential of this capability are recommended.
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This paper establishes novel methods for vehicle localization and mapping using a 1D linear automotive radar array in conjuncture with pre-existing lidar maps, and tests if the generated radar map can be made to be 3 dimensional. The basic design of this study was to implement a SLAM (Simultaneous Localization And Mapping) system that co-registers radar data to radar data, and/or register radar data to lidar data. After the execution of experiments, it was established that it is possible to localize the car by relating observed radar data to premade lidar maps, and to continually add to a cumulative map made with the radar data that can further aid the localization process. Furthermore, the radar map created using the 1D linear automotive array can be extended to 3D with proposed processing chain, though more experiments to establish the full potential of this capability are recommended.
In this paper, a wire detection algorithm is proposed for synthetic aperture radar (SAR) images. The algorithm is specifically designed for SAR images generated from an agile, drone-mounted, omnidirectional radar array to be used for the detection of improvised explosive devices (IEDs). A multistage approach consisting of denoising, constant false alarm rate (CFAR) thresholding, feature extraction, and automated detection using the Radon transform, is proposed and applied to a set of SAR images with multiple aspect angles. At each detection step, the look-angles of individual pixels are used to remove false alarms, and improve detection accuracy. The algorithm is tested using measured data and provides an acceptable detection performance on straight wire segments even in the presence of a strong background clutter.
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In this paper, a wire detection algorithm is proposed for synthetic aperture radar (SAR) images. The algorithm is specifically designed for SAR images generated from an agile, drone-mounted, omnidirectional radar array to be used for the detection of improvised explosive devices (IEDs). A multistage approach consisting of denoising, constant false alarm rate (CFAR) thresholding, feature extraction, and automated detection using the Radon transform, is proposed and applied to a set of SAR images with multiple aspect angles. At each detection step, the look-angles of individual pixels are used to remove false alarms, and improve detection accuracy. The algorithm is tested using measured data and provides an acceptable detection performance on straight wire segments even in the presence of a strong background clutter.
A wide-swath synthetic aperture radar (SAR) image is known to be achievable by merging multistatic aliased data that is collected with an appropriate along-track displacement. However, in terms of both flexibility requirements like potentiality of both along-track and cross-track (XT) interferometry and design requirements like orbital safety, etc., a XT baseline is not only demanded but also unavoidable. In this work, a method is proposed in order to merge SAR data to recover the Doppler spectrum unambiguously for the nonzero XT baseline case. The algorithm is compared and validated by simulating an azimuth invariant multistatic SAR satellite constellation. The results are promising in terms of dealing with XT baselines.
...
A wide-swath synthetic aperture radar (SAR) image is known to be achievable by merging multistatic aliased data that is collected with an appropriate along-track displacement. However, in terms of both flexibility requirements like potentiality of both along-track and cross-track (XT) interferometry and design requirements like orbital safety, etc., a XT baseline is not only demanded but also unavoidable. In this work, a method is proposed in order to merge SAR data to recover the Doppler spectrum unambiguously for the nonzero XT baseline case. The algorithm is compared and validated by simulating an azimuth invariant multistatic SAR satellite constellation. The results are promising in terms of dealing with XT baselines.
Journal article
(2020)
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Jeroen Overdevest, Feike Jansen, Faruk Uysal, Alexander Yarovoy
Utilization of phase-coded waveforms in automotive MIMO radars for short to medium range applications is studied. Performances of three most-promising binary code families (Gold, APAS and ZCZ sequences) are compared. Design tradeoffs of practical implementation of phased-coded waveforms for MIMO radar are analyzed for the first time for a possible future System on Chip implementation. Orthogonality of the waveforms in case of moving targets is analyzed. The implications of the code properties for the Range-Doppler map, as well as the Range-Angular map, are pointed out. Doppler frequency shift impact on such performance indicators as the target peak power and range sidelobe levels in the range-Doppler plane, as well as the range and azimuth sidelobe behavior, and the angular error in the azimuthal plane have been comprehensively studied for the first time. It is shown that the time-staggered transmit scheme with autocorrelation properties only (while introducing azimuthal errors) results in improved performance compared to code division multiplexing with auto- and cross-correlation properties.
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Utilization of phase-coded waveforms in automotive MIMO radars for short to medium range applications is studied. Performances of three most-promising binary code families (Gold, APAS and ZCZ sequences) are compared. Design tradeoffs of practical implementation of phased-coded waveforms for MIMO radar are analyzed for the first time for a possible future System on Chip implementation. Orthogonality of the waveforms in case of moving targets is analyzed. The implications of the code properties for the Range-Doppler map, as well as the Range-Angular map, are pointed out. Doppler frequency shift impact on such performance indicators as the target peak power and range sidelobe levels in the range-Doppler plane, as well as the range and azimuth sidelobe behavior, and the angular error in the azimuthal plane have been comprehensively studied for the first time. It is shown that the time-staggered transmit scheme with autocorrelation properties only (while introducing azimuthal errors) results in improved performance compared to code division multiplexing with auto- and cross-correlation properties.
Camera systems are widely used for surveillance in the security and defense domains. The main advantages of camera systems are their high resolution, their ease of use, and the fact that optical imagery is easy to interpret for human operators. However, particularly when considering application in the defense domain, cameras have some disadvantages. In poor lighting conditions, dust or smoke the image quality degrades and, additionally, cameras cannot provide range information. These issues may be alleviated by exploiting the strongpoints of radar. Radar performance is largely preserved during nighttime, in varying weather conditions and in dust and smoke. Furthermore, radar provides range information of detected objects. Since their qualities appear to be complementary, can radar and camera systems learn from each other? In the current study, the potential of radar/video multimodal learning is assessed for the classification of human activity.
...
Camera systems are widely used for surveillance in the security and defense domains. The main advantages of camera systems are their high resolution, their ease of use, and the fact that optical imagery is easy to interpret for human operators. However, particularly when considering application in the defense domain, cameras have some disadvantages. In poor lighting conditions, dust or smoke the image quality degrades and, additionally, cameras cannot provide range information. These issues may be alleviated by exploiting the strongpoints of radar. Radar performance is largely preserved during nighttime, in varying weather conditions and in dust and smoke. Furthermore, radar provides range information of detected objects. Since their qualities appear to be complementary, can radar and camera systems learn from each other? In the current study, the potential of radar/video multimodal learning is assessed for the classification of human activity.
This paper discusses the design details of a high resolution, low "Size, Weight, Power and Cost" (SWaP-C) radar altimeter (RA) system. Operating frequency of the radar is chosen within the Ka-band to achieve the desired size and weight requirements, that are highly demanded for the small satellite missions in a cost-efficient way. We propose a system design such that, an intended radar altimeter can be built by using the Commercial off the Shelf (COTS) components. The simulation results show that the proposed RA has high potentiality for realization.
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This paper discusses the design details of a high resolution, low "Size, Weight, Power and Cost" (SWaP-C) radar altimeter (RA) system. Operating frequency of the radar is chosen within the Ka-band to achieve the desired size and weight requirements, that are highly demanded for the small satellite missions in a cost-efficient way. We propose a system design such that, an intended radar altimeter can be built by using the Commercial off the Shelf (COTS) components. The simulation results show that the proposed RA has high potentiality for realization.
Conference paper
(2020)
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Franz Lampel, Faruk Uysal, Firat Tigrek, Simone Orru, Alex Alvarado, Frans Willems, Alexander Yarovoy
This paper describes an FMCW based radar and communication (RadCom) system and addresses the challenges in the synchronization of multiple units for communication functionality. We proposed a novel technique to detect the FMCW RadCom signal at the communication receiver and derive the detection and false alarm probabilities of it. Moreover, to achieve fine synchronization between transmit and receive devices, a novel approach based on FMCW RadCom signal time of arrival estimation is proposed. The potential capability of a RadCom system is experimentally demonstrated for the first time by a set of automotive-grade mmWave radars with GPS-based synchronization.
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This paper describes an FMCW based radar and communication (RadCom) system and addresses the challenges in the synchronization of multiple units for communication functionality. We proposed a novel technique to detect the FMCW RadCom signal at the communication receiver and derive the detection and false alarm probabilities of it. Moreover, to achieve fine synchronization between transmit and receive devices, a novel approach based on FMCW RadCom signal time of arrival estimation is proposed. The potential capability of a RadCom system is experimentally demonstrated for the first time by a set of automotive-grade mmWave radars with GPS-based synchronization.
Journal article
(2020)
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Faruk Uysal
A frequency-modulated continuous-wave (FMCW) radar takes advantage of stretch processing (dechirping, deramping) to reduce the sampling requirements of radar systems such as automotive radars. When applying phase coding into FMCW radar systems for interference mitigation or joint communication, preservation of this benefit is not possible, due to the nature of this process. This paper proposes a new phase coded FMCW system as well as a processing strategy based on a group delay filter to deal with unaligned phase-coded radar return signals. Moreover, this paper proposes an improved interference mitigation method based on a phase-coded linear- frequency modulated (LFM) continuous waveform and points out the improvements in the signal-to-interference ratio (SIR). In the proposed mitigation technique, unlike the traditional approach where RF spectrum spreads, the beat frequency spectrum of the FMCW radar spreads, thus the bandwidth of RF hardware stays the same as a classical LFM continuous wave radar. The success of the proposed phase coded frequency-modulated continuous-wave (PC-FMCW) radar is illustrated in simulations and increased interference mitigation performance is validated by experiments.
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A frequency-modulated continuous-wave (FMCW) radar takes advantage of stretch processing (dechirping, deramping) to reduce the sampling requirements of radar systems such as automotive radars. When applying phase coding into FMCW radar systems for interference mitigation or joint communication, preservation of this benefit is not possible, due to the nature of this process. This paper proposes a new phase coded FMCW system as well as a processing strategy based on a group delay filter to deal with unaligned phase-coded radar return signals. Moreover, this paper proposes an improved interference mitigation method based on a phase-coded linear- frequency modulated (LFM) continuous waveform and points out the improvements in the signal-to-interference ratio (SIR). In the proposed mitigation technique, unlike the traditional approach where RF spectrum spreads, the beat frequency spectrum of the FMCW radar spreads, thus the bandwidth of RF hardware stays the same as a classical LFM continuous wave radar. The success of the proposed phase coded frequency-modulated continuous-wave (PC-FMCW) radar is illustrated in simulations and increased interference mitigation performance is validated by experiments.
Phase-Coded FMCW Automotive Radar
Application and Challenges
Phase-Coded frequency-modulated continuous-wave (PC-FMCW) radar is an emerging radar system with its unique features such as enabling joint sensing and communication or advanced interference mitigation. Even though radars with phase coding capabilities are available in the automotive radar market today, there are some challenges in phase coded radar applications. With this paper we demonstrate multiple bit coding per single transmit chirp waveform in a FMCW automotive radar system for the first time. We concentrate on the sensing aspect of PC-FMCW radar and point out the challenges due to instantaneous phase change. To overcome these issues and improve sensing performance, this paper proposes a smart filtering method which consists of rejection filtering and signal recovery steps.
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Phase-Coded frequency-modulated continuous-wave (PC-FMCW) radar is an emerging radar system with its unique features such as enabling joint sensing and communication or advanced interference mitigation. Even though radars with phase coding capabilities are available in the automotive radar market today, there are some challenges in phase coded radar applications. With this paper we demonstrate multiple bit coding per single transmit chirp waveform in a FMCW automotive radar system for the first time. We concentrate on the sensing aspect of PC-FMCW radar and point out the challenges due to instantaneous phase change. To overcome these issues and improve sensing performance, this paper proposes a smart filtering method which consists of rejection filtering and signal recovery steps.
Journal article
(2019)
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Sharef Neemat, Faruk Uysal, Oleg Krasnov, Alexander Yarovoy
A reconfigurable range-Doppler processing method for FMCW radar is presented. By concatenating beat-frequency signals from more than one sweep, a continuous beat-frequency signal for the whole coherent processing interval (CPI) can be created. As a result, continuous targets' observation time is extended beyond that of a single chirp duration, leading to range resolution improvement. The created continuous beat-frequency signal can be split in the digital domain to any two-dimensional slow-time and fast-time matrices with the same number of elements as in the original signals, which offers a realization of a software-defined pulse/sweep repetition rate in range-Doppler processing. The signal concatenation is done in the short-time Fourier transform (STFT) domain, where the beat-frequency slices are extrapolated to compensate for the observation time lost in the transient region between sweeps, and then a phase correction is applied to each frequency-slice as appropriate, followed by an inverse STFT (ISTFT). The proposed technique is verified with simulation and experiments with an FMCW radar for stable and moving target scenarios. We found that the method allows for range resolution improvement without the transmission of additional bandwidth and also allows for the ability to observe different resolution granularities in parallel from one CPI. It additionally allows the decoupling of the transmitted PRF from the Doppler processing PRF, permitting the facility to observe different unambiguous Doppler velocity intervals from one CPI, without compromising on the total CPI processing gain.
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A reconfigurable range-Doppler processing method for FMCW radar is presented. By concatenating beat-frequency signals from more than one sweep, a continuous beat-frequency signal for the whole coherent processing interval (CPI) can be created. As a result, continuous targets' observation time is extended beyond that of a single chirp duration, leading to range resolution improvement. The created continuous beat-frequency signal can be split in the digital domain to any two-dimensional slow-time and fast-time matrices with the same number of elements as in the original signals, which offers a realization of a software-defined pulse/sweep repetition rate in range-Doppler processing. The signal concatenation is done in the short-time Fourier transform (STFT) domain, where the beat-frequency slices are extrapolated to compensate for the observation time lost in the transient region between sweeps, and then a phase correction is applied to each frequency-slice as appropriate, followed by an inverse STFT (ISTFT). The proposed technique is verified with simulation and experiments with an FMCW radar for stable and moving target scenarios. We found that the method allows for range resolution improvement without the transmission of additional bandwidth and also allows for the ability to observe different resolution granularities in parallel from one CPI. It additionally allows the decoupling of the transmitted PRF from the Doppler processing PRF, permitting the facility to observe different unambiguous Doppler velocity intervals from one CPI, without compromising on the total CPI processing gain.
Conference paper
(2019)
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Lorenzo Iannini, Alessandro Mancinelli, Paco Lopez Dekker, Peter Hoogeboom, Yuanhao Li, Faruk Uysal, Alexander Yarovoy
The work investigates staggered and random PRF (Pulse Repetition Frequency) strategies for a close formation of small Synthetic Aperture Radar (SAR) satellites operating in a multistatic configuration. The satellites are positioned within a fraction of the along-track critical baseline, hence allowing for the application of Displaced Phase Center image formation approaches. The performance of regular and random pulse sampling schemes is in particular assessed for a single-input multiple-output (SIMO) S-Band constellation, whose feasibility is further analyzed in relation to the number of satellites and their antenna size.
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The work investigates staggered and random PRF (Pulse Repetition Frequency) strategies for a close formation of small Synthetic Aperture Radar (SAR) satellites operating in a multistatic configuration. The satellites are positioned within a fraction of the along-track critical baseline, hence allowing for the application of Displaced Phase Center image formation approaches. The performance of regular and random pulse sampling schemes is in particular assessed for a single-input multiple-output (SIMO) S-Band constellation, whose feasibility is further analyzed in relation to the number of satellites and their antenna size.
Conference paper
(2019)
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Faruk Uysal, Pascal J. Aubry, Alexander Yarovoy
Automotive radars suffer from low angular estimation accuracy due to the limited number of antennas and insufficient onboard processing power. This paper addresses the single target tracking problem in automotive radar by using recently proposed MIMO-monopulse approach which blends the monopulse approach with the collocated MIMO radar. We demonstrate and compare the localization performance of the MIMO-monopulse at an automotive radar on a real-world scenario. Experiments show that MIMO-monopulse results in a better angular accuracy comparing to the conventional digital
beamforming even though the low-level processing power. ...
beamforming even though the low-level processing power. ...
Automotive radars suffer from low angular estimation accuracy due to the limited number of antennas and insufficient onboard processing power. This paper addresses the single target tracking problem in automotive radar by using recently proposed MIMO-monopulse approach which blends the monopulse approach with the collocated MIMO radar. We demonstrate and compare the localization performance of the MIMO-monopulse at an automotive radar on a real-world scenario. Experiments show that MIMO-monopulse results in a better angular accuracy comparing to the conventional digital
beamforming even though the low-level processing power.
beamforming even though the low-level processing power.
This paper generalizes a previous formulation of signal separation problem for dynamic wind turbine clutter mitigation at weather radar systems. In this modified formulation, we use nonconvex regularizers together with multichannel overlapping group shrinkage (MOGS) to penalize weather signals and adopt multidimensional processing. We show the restored weather signals in plan position indicator (PPI) format and, to demonstrate the improvement, compare them with the ones produced by the previous method in reflectivity, spectral width, and Doppler velocity estimates of weather data. The improvement results from a better characterization of the sparsities of the weather radar returns. During the course of experiments, we observe that the proposed method successfully mitigates the wind turbine clutter and dramatically increases the signal-to-clutter ratio, even for different weather and wind turbine signatures. In addition, when the wind turbine clutter is weak in the mixture, our algorithm manages to attenuate the ground clutters and produces clutter-free weather signals favorable for further processing.
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This paper generalizes a previous formulation of signal separation problem for dynamic wind turbine clutter mitigation at weather radar systems. In this modified formulation, we use nonconvex regularizers together with multichannel overlapping group shrinkage (MOGS) to penalize weather signals and adopt multidimensional processing. We show the restored weather signals in plan position indicator (PPI) format and, to demonstrate the improvement, compare them with the ones produced by the previous method in reflectivity, spectral width, and Doppler velocity estimates of weather data. The improvement results from a better characterization of the sparsities of the weather radar returns. During the course of experiments, we observe that the proposed method successfully mitigates the wind turbine clutter and dramatically increases the signal-to-clutter ratio, even for different weather and wind turbine signatures. In addition, when the wind turbine clutter is weak in the mixture, our algorithm manages to attenuate the ground clutters and produces clutter-free weather signals favorable for further processing.