Moving Target Detection With Distributed Mimo Radar In Non-Homogeneous Environment
Unlike most previous efforts which deal with moving target detection (MTD) with distributed multi-input multi-output (MIMO) radars in a homogeneous environment, we consider here the problem with non-homogeneous clutter, which arises from the multi-static transmitter-receiver configuration inherent in the distributed MIMO radar. This study is motivated by the fact that the multi-static transmit–receive configuration in a distributed MIMO radar causes non-stationary clutter which in turns causes the clutter power fluctuation and its covariance structure variation.
To account for these issues, we will first introduce a new non-homogeneous clutter model, where the clutter resides in a low-rank subspace with different subspace coefficients (and hence different clutter power) for different transmit–receive pair and, accordingly, a global detection strategy that non-coherently combines the local matched subspace detection. Theoretical analysis including the constant false alarm rate (CFAR) property and the probability distribution of the test statistic will be reviewed. Then, a set of distinct auto-regressive (AR) models will be incorporated to capture both the clutter power fluctuation and the covariance structure variation across transmit-receive pairs. The corresponding target detection scheme and target velocity estimation will be introduced.
Pu Wang received the Ph.D. degree from the Stevens Institute of Technology, Hoboken, NJ, in electrical engineering in 2011. He was an intern at the Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, in the summer of 2010. Since 2012, he has been with the Schlumberger-Doll research, Cambridge, MA, as a postdoc research scientist. His current research interests include statistical signal processing, and its applications in (borehole) geophysics, cognitive radio networks and radar.
Dr. Wang received the Outstanding Doctoral Thesis in EE Award in 2011, the Edward Peskin Award in 2011, the Francis T. Boesch Award in 2008, and the Outstanding Research Assistant Award in 2007, all from the Stevens Institute of Technology. In 2013, his paper, titled “Multiantenna-Assisted Spectrum Sensing for Cognitive Radio”, received the IEEE Jack Neubauer Memorial Award for the best systems paper published in theIEEE Transactions on Vehicular Technology.