K分布杂波中分布式目标的Rao检测

Rao Test of Distributed Targets in K-distributed Clutter

该文针对高分辨雷达体制下,点目标分裂成分布式目标所带来的检测问题,提出了基于Rao检测的分布式目标自适应检测算法。将分布式目标建模为子空间信号,目标不仅在距离维上扩展同时也在Doppler频率维上扩展。Rao检测算法只需对H0假设条件下的未知参数进行最大似然估计,在构造检测器的过程中运用两步法检测策略,有效地减少了计算量和复杂度。最后,用Monte Carlo仿真了该算法的检测性能,并与以前的检测器相比较验证了新提出的检测器对分布式目标在K分布杂波中的有效性。

For the detection problem caused by point targets broken up into distributed targets in the high-range resolution radar system,an adaptive detection algorithm based on the Rao test is proposed.The distributed target,which is modeled as a subspace random signal,may be expanded both in range and also in Doppler frequency axes.The unknown parameters are estimated by maximum likelihood estimation only under hypothesis H0 in Rao test.Moreover,the detector is obtained relying on the two-step design procedure.Because of these,both the computational burden and the complexity are cut down.Finally,performances of the proposed detector are assessed through Monte Carlo simulations and are shown to have better detection performance of distributed targets in K-distributed clutter compared with the existing similar detector.