Coherent Detection for MIMO Radars

Superiority of multiple-input multiple-output (MIMO) radars over conventional phased array radars has been recently shown in many aspects. MIMO radars have better detection performance and can extract target information more precisely than phased array radars. In this paper, the problem of target detection using temporal coherent pulse terrain is considered for MIMO radars. We have introduced a structure that is suitable for coherent processing. Based on this structure, we have formulated this problem as a hypothesis test. One decision rule is developed for detection of target with unknown amplitude embedded in additive white gaussian noise (AWGN) with known power using the generalized likelihood ratio test (GLRT). Another adaptive scheme for the case of unknown power is presented. We have also proposed an ad-hoc constant false alarm rate (CFAR) detector against AWGN with unknown power. Performance of these detectors have been evaluated analytically. The results show the superiority of the MIMO radars with temporal coherent processing over the conventional phased arrays.

[1]  Rick S. Blum,et al.  Performance of MIMO radar systems: advantages of angular diversity , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[2]  D. J. Rabideau,et al.  Ubiquitous MIMO multifunction digital array radar , 2003, The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003.

[3]  Christ D. Richmond,et al.  Performance of the adaptive sidelobe blanker detection algorithm in homogeneous environments , 2000, IEEE Trans. Signal Process..

[4]  Rick S. Blum.  Distributed detection of narrowband signals , 1995, IEEE Trans. Inf. Theory.

[5]  Christ D. Richmond,et al.  Performance of a class of adaptive detection algorithms in nonhomogeneous environments , 2000, IEEE Trans. Signal Process..

[6]  Mohammad Reza Aref,et al.  Detection of coherent radar signals with unknown Doppler shift , 1996 .

[7]  A. Sheikhi,et al.  Model-based Adaptive Target Detection in Clutter Using MIMO Radar , 2006, 2006 CIE International Conference on Radar.

[8]  Wang Jun,et al.  Analysis and experimental results on sparse-array synthetic impulse and aperture radar , 2001, 2001 CIE International Conference on Radar Proceedings (Cat No.01TH8559).

[9]  Rick S. Blum,et al.  MIMO radar: an idea whose time has come , 2004, Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509).

[10]  F.C. Robey,et al.  MIMO radar theory and experimental results , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[11]  H.A. Khan,et al.  Ultra wideband multiple-input multiple-output radar , 2005, IEEE International Radar Conference, 2005..

[12]  Chen Baixiao,et al.  Long-time coherent integration based on sparse-array synthetic impulse and aperture radar , 2001, 2001 CIE International Conference on Radar Proceedings (Cat No.01TH8559).

[13]  Hugh Griffiths.  From a different perspective: principles, practice and potential of bistatic radar , 2003, 2003 Proceedings of the International Conference on Radar (IEEE Cat. No.03EX695).

[14]  Michael J. Steiner.  A Framework for the Detection of a Target of Unknown Velocity , 1990 .

[15]  E. J. Kelly.  An Adaptive Detection Algorithm , 1986, IEEE Transactions on Aerospace and Electronic Systems.

[16]  Pramod K. Varshney,et al.  Distributed detection with multiple sensors I. Fundamentals , 1997, Proc. IEEE.

[17]  Alexander M. Haimovich,et al.  Spatial Diversity in Radars—Models and Detection Performance , 2006, IEEE Transactions on Signal Processing.

[18]  J.-M. Colin.  Phased array radars in France: present and future , 1996, Proceedings of International Symposium on Phased Array Systems and Technology.

[19]  Hugh D. Griffiths,et al.  Target Model Effects on MIMO Radar Performance , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[20]  G. Barton,et al.  The RADSIM high fidelity radar and EW simulation , 1993 .