对于空间分集雷达,各雷达站与目标的距离不同会引起信噪比的不同,从而降低传统的非相干积累检测器的检测性能.基于尼曼-皮尔逊准则,提出一种对各站接收信号进行基于信噪比加权的信号融合检测器.在已知各站回波信噪比的条件下,它可以达到检测性能的上界.数值试验表明,该检测器的检测性能较传统的非相干积累检测器有明显改善,特别在信噪比较低时.
For a spatial diversity radar,signals received by widely separated radar sites may have different signal-noise-ratios(SNRs) due to different distances between radar sites and target,which would decrease the detection performance of the conventional incoherent accumulating detector(IAD).Based on the Neyman-Pearson criterion,a signal fusion based target detection algorithm is proposed,which weights signals received by different radar sites according to channel SNRs estimated.With channel SNRs of radar sites known,this algorithm achieves the upper bound of the detection performance.Numerical experiments indicate that the proposed algorithm gives a much better detection performance than the conventional IAD,especially when channel SNRs are low.