TY - GEN
T1 - Bayesian Detection for Distributed MIMO Radar with Non-Orthogonal Waveforms in Non-Homogeneous Clutter
AU - Zeng, Cengcang
AU - Wang, Fangzhou
AU - Li, Hongbin
AU - Govoni, Mark A.
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This paper considers target detection in distributed multi-input multi-output (MIMO) radar with non-orthogonal waveforms in non-homogenous clutter. We first present a general signal model for distributed MIMO radar in cluttered environments. To cope with the non-homogenous clutter and possible clutter bandwidth mismatch, the covariance matrix of the disturbance (clutter and noise) signal is modeled as a random matrix following an inverse complex Wishart distribution. Then, we propose three Bayesian detectors, including a non-coherent detector, a coherent detector, and a hybrid detector. The latter is a compromise of the former two, as it forsakes phase estimation needed by the coherent detector, but requires the samples within a coherent processing interval (CPI) to maintain phase coherence that is unnecessary for the non-coherent detector. Simulation results are presented to illustrate the performance of these Bayesian detectors and their non-Bayesian counterparts in non-homogeneous clutter when the clutter bandwidth is known exactly and, respectively, with uncertainty.
AB - This paper considers target detection in distributed multi-input multi-output (MIMO) radar with non-orthogonal waveforms in non-homogenous clutter. We first present a general signal model for distributed MIMO radar in cluttered environments. To cope with the non-homogenous clutter and possible clutter bandwidth mismatch, the covariance matrix of the disturbance (clutter and noise) signal is modeled as a random matrix following an inverse complex Wishart distribution. Then, we propose three Bayesian detectors, including a non-coherent detector, a coherent detector, and a hybrid detector. The latter is a compromise of the former two, as it forsakes phase estimation needed by the coherent detector, but requires the samples within a coherent processing interval (CPI) to maintain phase coherence that is unnecessary for the non-coherent detector. Simulation results are presented to illustrate the performance of these Bayesian detectors and their non-Bayesian counterparts in non-homogeneous clutter when the clutter bandwidth is known exactly and, respectively, with uncertainty.
KW - Bayesian detection
KW - Distributed MIMO radar
KW - non-homogeneous clutter
KW - non-orthogonal waveforms
UR - http://www.scopus.com/inward/record.url?scp=85163748842&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85163748842&partnerID=8YFLogxK
U2 - 10.1109/RadarConf2351548.2023.10149555
DO - 10.1109/RadarConf2351548.2023.10149555
M3 - Conference contribution
AN - SCOPUS:85163748842
T3 - Proceedings of the IEEE Radar Conference
BT - RadarConf23 - 2023 IEEE Radar Conference, Proceedings
T2 - 2023 IEEE Radar Conference, RadarConf23
Y2 - 1 May 2023 through 5 May 2023
ER -