在球不变随机向量非高斯杂波背景下,针对SDD-GLRT方法在统计平均意义下对距离扩展目标进行最优检测所带来的检测损失,通过充分利用目标散射点的先验信息,基于有序统计检测理论,提出了修正的SDD-GLRT距离扩展目标检测方法.理论分析表明,在不存在目标的假设下,虚警概率与纹理分量的混合分布、杂波协方差矩阵以及确知信号的方向向量无关,即修正的SDD-GLRT方法具有恒虚警率(constant false alarm rate,CFAR)特性.仿真结果表明,随着积累脉冲数及目标散射点所占距离单元个数的增加,修正的SDD-GLRT检测性能得到提高.在散射点分布稀疏条件下,修正的SDD-GLRT的检测性能要明显好于SDD-GLRT和NSDD-GLRT,且在估计目标散射点个数存在微弱偏差和不同杂波尖峰情况下,修正的SDD-GLRT具有很好的鲁棒性.

Scatterer density dependent generalized likelihood ratio test (SDD-GLRT) performans well in detecting a spatially distributed target in the presence of additive non-Gaussian clutter,where the clutter is modeled as a spherically invariant random vector (SIRV).But SDD-GLRT is a statistically optimum detector,which results in performance loss in the practical case.Base on the order statistics detection theory,a modified SDD-GLRT detector is proposed,which utilizes a priori knowledge of the scatterer spatial distribution fully.It shows that the probability of false alarm is independent of the underlying mixing distribution,the normalized clutter covariance matrix and the steering vector.Hence the modified SDD-GLRT is a constant false alarm rate (CFAR) detector.The experimental results show that the modified SDD-GLRT detection performance is significantly improved by increasing the number of scatterers or the number of pulses used.For detecting a sparsely distributed target,the modified SDD-GLRT outperforms both of the SDD-GLRT and the NSDD-GLRT.Furthermore,the modified SDD-GLRT is more robust for a moderate mismatch of the expected number of scatterers or different spikiness of the clutter.