MIMO Phased-Array for SMTI Radar

Waveform diversity techniques for radar have gained considerable interest over the past several years. Novel radar waveforms have been proposed to improve detection performance and metric accuracy (i.e., angle estimation performance). This paper explores the potential for using a waveform diversity technique known as multiple input, multiple output (MIMO) radar to improve the detection performance of slow moving surface targets from a moving radar platform. The MIMO radar system achieves superior performance by transmitting unique uncorrelated waveforms from each antenna subaperture as opposed to the traditional approach of transmitting a single coherent waveform across the entire aperture. The results show that the radar system minimum detectable velocity (MDV) can be reduced by exploiting the ability of a MIMO system to effectively increase the radar antenna aperture.

[1]  Daniel W. Bliss,et al.  Multiple-input multiple-output (MIMO) radar and imaging: degrees of freedom and resolution , 2003, The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003.

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

[3]  Peter Zulch,et al.  MIMO Phased-Array for SMTI Radar , 2008 .

[4]  D.W. Bliss,et al.  Multiple-input multiple-output (MIMO) radar: performance issues , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[5]  D. K. Fenner,et al.  Test results of a space-time adaptive processing system for airborne early warning radar , 1996, Proceedings of the 1996 IEEE National Radar Conference.

[6]  J. Tabrikian,et al.  Target Detection and Localization Using MIMO Radars and Sonars , 2006, IEEE Transactions on Signal Processing.

[7]  James Ward,et al.  Space-time adaptive processing for airborne radar , 1998 .

[8]  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..

[9]  Harry L. Van Trees,et al.  Optimum Array Processing , 2002 .