A track-before-detect algorithm for statistical MIMO radar multitarget detection

This paper investigates the early detection problem of multiple moving targets in statistical MIMO radar systems using the track-before-detect (TBD) techniques. At first, assuming prior knowledge of the number of targets, a binary generalized likelihood ratio test (GLRT) is derived, which shows that the optimal implementation of the GLRT requires multidimensional joint search. To reduce the implementation complexity, a suboptimum multitarget TBD algorithm using successive-target-cancellation and polar Hough transform (STC-PHT) is proposed. In addition to low complexity, the new proposed algorithm doesn't need the prior information of the number of targets, and can avoid the implementation of multi-hypothesis test when the number of targets is unknown. The simulation results show that this algorithm can effectively improve the detection performance of statistical MIMO radar at low signal-to-noise ratio (SNR).