Passive MIMO Radar Detection with Unknown Colored Gaussian Noise

The target detection of the passive multiple-input multiple-output (MIMO) radar that is comprised of multiple illuminators of opportunity and multiple receivers is investigated in this paper. In the passive MIMO radar, the transmitted signals of illuminators of opportunity are totally unknown, and the received signals are contaminated by the colored Gaussian noise with an unknown covariance matrix. The generalized likelihood ratio test (GLRT) is explored for the passive MIMO radar when the channel coefficients are also unknown, and the closed-form GLRT is derived. Compared with the GLRT with unknown transmitted signals and channel coefficients but a known covariance matrix, the proposed method is applicable for a more practical case whenthe covariance matrix of colored noise is unknown, although it has higher computational complexity. Moreover, the proposed GLRT can achieve similar performance as the GLRT with the known covariance matrix when the number of training samples is large enough. Finally, the effectiveness of the proposed GLRT is verified by several numerical examples.

[1]  E. J. Kelly,et al.  A noncoherent adaptive detection technique , 1992 .

[2]  Arye Nehorai,et al.  Target detection using weather radars and electromagnetic vector sensors , 2017, Signal Processing.

[3]  Michael A. Saville,et al.  Centralized Passive MIMO Radar Detection Without Direct-Path Reference Signals , 2014, IEEE Transactions on Signal Processing.

[4]  Daniel R. Fuhrmann,et al.  A CFAR adaptive matched filter detector , 1992 .

[5]  Braham Himed,et al.  GLRT Detector in Single Frequency Multi-static Passive Radar Systems , 2018, Signal Process..

[6]  Rick S. Blum,et al.  Passive MIMO radar detection exploiting known format of the communication signal observed in colored noise with unknown covariance matrix , 2020, Signal Process..

[7]  Martina Daun,et al.  Tracking in multistatic passive radar systems using DAB/DVB-T illumination , 2012, Signal Process..

[8]  Jianyu Yang,et al.  Adaptive detection and estimation for an unknown occurring interval signal in correlated Gaussian noise , 2015, Signal Process..

[9]  Jun Wang,et al.  Mismatched filter for analogue TV-based passive bistatic radar , 2011 .

[10]  Hongbin Li,et al.  Signal detection with noisy reference for passive sensing , 2015, Signal Process..

[11]  Hongbin Li,et al.  On the performance of the cross-correlation detector for passive radar applications , 2015, Signal Process..

[12]  Hongwei Liu,et al.  Linear fusion for target detection in passive multistatic radar , 2017, Signal Process..

[13]  Saeed Sadri,et al.  Theoretical approach for target detection and interference cancellation in passive radars , 2013 .