基于修正自适应匹配滤波器的机动目标检测方法

摘要

机动目标回波的多普勒走动和训练样本不足导致常规自适应匹配滤波器(Adaptive Matched Filter, AMF)检测机动目标时运算量大且性能不佳。针对此问题，该文提出一种基于修正AMF的机动目标检测方法。该方法首先通过对角加载减少样本空间自由度，从而降低对训练样本数的需求；然后以3次相位变换(Cubic Phase Transform, CPT)分离估计加速度，并以估计值补偿多普勒走动，降低联合匹配搜索维度，进而减少运算量；最后进行积累检测。仿真结果表明，该方法运算量低，可实现小样本下机动目标的有效检测，具有恒虚警(Constant False Alarm Rate, CFAR)特性。%Owing to the Doppler frequency migration of the return signal of maneuvering targets and finite training samples, it is difficult to detect maneuvering targets by conventional Adaptive Matched Filter (AMF) detectors. To solve this problem, a new method is proposed. First, to minimize sample size impairments, the diagonal loading technique was adopted to decrease the degrees of freedom of the sample space. Second, the Doppler frequency migration was compensated by the estimated acceleration which was estimated by the cubic phase transform, so as to reduce the dimension of matched searching and degrade the heavy calculation load. Finally, accumulation detection was conducted. The simulation results suggest that the proposed method can efficiently detect maneuvering target in finite sample situations with simple computation and constant false alarm rate detection.