MIMO雷达多目标检测前跟踪算法研究

 本文基于检测前跟踪技术研究了MIMO雷达系统中多个运动目标的早期预警问题,在推导已知目标数量时的二元广义似然比检验的基础上,提出了一种次优的基于“逐目标消除和极坐标Hough变换（STC-PHT）”的多目标检测前跟踪算法,并推导了该算法的虚警概率和检测概率表达式。与以往的多目标检测前跟踪算法相比,新算法具有较低的计算量,且本质上无需目标数量的先验信息,避免了目标数量未知时需执行多元假设检验的问题。仿真分析表明,新算法能有效地改善MIMO雷达在低信噪比条件下的检测性能。

Track-Before-Detect Algorithm in a MIMO Radar Multi-Target Environment

This paper investigated the early detection problem of multiple moving targets in MIMO radar systems using the track-before-detect (TBD) techniques. Based on the binary generalized likelihood ratio test (GLRT) with a priori known number of targets, a suboptimum multi-target TBD algorithm using successive-target-cancellation and polar Hough transform (STC-PHT) was proposed, and false alarm probability and detection probability formulae were derived. Compared with previous multi-target TBD algorithms, the new proposed algorithm has low computational complexity, no need for the prior information of the number of targets, and avoids the implementation of multiple hypothesis tests when the number of targets is unknown. The simulation results show that the new proposed algorithm can effectively improve the detection performance of MIMO radar at low signal-to-noise ratio.