MIMO multipath clutter mitigation for GMTI automotive radar in urban environments

Yu, Jason; Krolik, Jeffrey L.

doi:10.1049/cp.2012.1565

Cited by 26 publications

(9 citation statements)

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“…Therefore, the conversion of the coordinates for target-i from the radar Polar coordinate system to the world Cartesian coordinate system is shown in (7), where R A (φ A ) and T A are the rotation and translation matrices for the radar A defined in (8). Even though ( 7) and ( 8) are defined for radar A, they are analogous for radar B.…”

Section: Multipath Mitigationmentioning

confidence: 99%

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Radar Fusion for Multipath Mitigation in Indoor Environments

Copa

Aziz

Rykunov

et al. 2020

2020 IEEE Radar Conference (RadarConf20)

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One of the main challenges of radar-based localization applications in indoor environments is the presence of strong multipath. When the radar bandwidth is large enough, multipath components can be resolved in range but they result in unwanted ghost targets. We propose a novel multipath mitigation approach that exploits the fact that multipaths are highly dependent on the scene geometry. The multipath mitigation approach discards the ghost targets based on the fused information of multiple radars located at different positions in the scene. For such radar fusion, the output of the radar signal processing chain is translated into the world coordinate system that is common for all the radars. We propose a radar alignment approach to estimate the translation and rotation parameters from radar to world coordinate system and vice versa. Our multipath mitigation method is combined with an unscented Kalman filter to improve the localization accuracy. We demonstrate the effectiveness of our complete approach with a real experiment using two radars to detect and track a target in a room with severe multipath.

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Section: Multipath Mitigationmentioning

confidence: 99%

“…The features are fed to a Neural Network to correct the beat frequency. MIMO Space-Time Adaptive Processing (STAP) techniques are considered in [7]. Finally, Back Projection (BP) algorithm is used in [8], [9] that exploit the fact that multipaths are highly dependent on the scene geometry.…”

Section: Introductionmentioning

confidence: 99%

Radar Fusion for Multipath Mitigation in Indoor Environments

Copa

Aziz

Rykunov

et al. 2020

2020 IEEE Radar Conference (RadarConf20)

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“…Direct-path backscatter will exhibit a DOA that is identical to the DOD, while multipath backscatter will exhibit a DOA that is different than the DOD. If MIMO radar is added to the STAP formulation, there will be three adaptive dimensions (DOA, DOD, and Doppler shift) as opposed to two with traditional STAP (DOA and if they share the same DOA and Doppler shift, by taking advantage of the DOD dimension [52,53] Consider the steering vector of transmitter and receiver array separately, redefine the spatial-temporal steering vector as…”

Section: Space-time Signalsmentioning

confidence: 99%

Target Localization Using MIMO-Monopulse: Application on 79 GHz FMCW Automotive Radar

Feng

Uysal

Yarovoy

2018

2018 15th European Radar Conference (EuRAD)

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Automotive radar is widely used for driving safety support and it is a key element of future autonomous vehicles. Radar sensors have the property that the performance is not to be affected by low vision conditions compared with camera sensors or laser based radar sensors, which makes it crucial for the autonomous driving system.Automotive radar system utilizes millimeter-wave band to detect the range, velocity and direction of arrival (DOA). Commercial 24 GHz and 77GHz radar have been well developed in vehicle applications at present, and the future trend is 79 GHz solution with wider 4 GHz bandwidth, which has been defined by the European Commission in 2004 as the frequency allocation for automotive shortrange radar systems.The main modulation method of automotive radar is Frequency-Modulated Continous-Wave(FMCW), which holds advantages including high-resolution distance measurement, quick updating and lower sampling frequency required on hardware.

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“…The structure of STAMP system has some similarity to the SLAM set-up [23], where Dissanayake et al provided convergence properties of SLAM for linear Gaussian system, so that the uncertainty of the time invariant multipath parameter estimate decreases monotonically as successive observations are obtained. In our problem, however, the challenge is to handle multipath propagation paths, which are not considered in modeling for SLAM.…”

Section: Blind Nlos Initiationmentioning

confidence: 99%

“…In order to recursively estimate the optimal 1: * , the joint association likelihood can be decomposed as: 23) and ⊕ and denote vertical and diagonal concatenation operation when the observation-raymode pair is valid , ( , ) = 1 according to , .…”

Section: Problem Formulationmentioning

confidence: 99%

Simultaneous Target and Multipath Positioning

Krolik

2014

IEEE J. Sel. Top. Signal Process.

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In this work, we present the Simultaneous Target and Multipath Positioning (STAMP) technique to jointly estimate the unknown target position and uncertain multipath channel parameters. We illustrate the applications of STAMP for target tracking/geolocation problems using single-station hybrid TOA/AOA system, monostatic MIMO radar and multistatic range-based/AOA based localization systems.The STAMP algorithm is derived using a recursive Bayesian framework by including the target state and multipath channel parameters as a single random vector, and the unknown correspondence between observations and signal propagation channels is solved using the multi-scan multi-hypothesis data association. In the presence of the unknown time-varying number of multipath propagation modes, the STAMP algorithm is modified based on the single-cluster PHD filtering by modeling the multipath parameter state as a random finite set. In this case, the target state is defined as the parent process, which is updated by using a particle filter or multi-hypothesis Kalman filter. The multipath channel parameter is defined as the daughter process and updated based on an explicit Gaussian mixture PHD filter. Moreover, the idenfiability analysis of the joint estimation problem is provided in terms of Cramér-Rao lower bound (CRLB).The Fisher information contributed by each propagation mode is investigated, and the v effect of Fisher information loss caused by the measurement origin uncertainty is also studied. The proposed STAMP algorithms are evaluated based on a set of illustrative numeric simulations and real data experiments with an indoor multi-channel radar testbed. Substantial improvement in target localization accuracy is observed.vi

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MIMO multipath clutter mitigation for GMTI automotive radar in urban environments

Cited by 26 publications

References 0 publications

Radar Fusion for Multipath Mitigation in Indoor Environments

Radar Fusion for Multipath Mitigation in Indoor Environments

Target Localization Using MIMO-Monopulse: Application on 79 GHz FMCW Automotive Radar

Simultaneous Target and Multipath Positioning

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