Target tracking in widely separated non-coherent multiple-input multiple-output radar systems

In a widely separated multiple-input multiple-out (MIMO) radar system with non-coherent receivers, the maximum likelihood estimator (MLE) of target location and the corresponding CRLB matrix are derived. Further, two interactive signal processing and tracking algorithms are developed based on the Kalman filter and the particle filter respectively. For a system with a small number of elements and a low SNR value, the particle filter outperforms the KF significantly. In both methods, the tracker provides predictive information regarding the target location, so that the matched filter can match to the most probable target locations, reducing the cost and improving the tracking performance. It is shown that the non-coherent MIMO radar provides a significant performance improvement over a monostatic radar with high range and azimuth resolutions.