Robust统计在主动声纳分裂波束目标方位走向估计中的应用

主动声纳通常采用分裂波束双通道互谱法进行目标方位估计，但信号处理过程中目标回波脉冲长度往往和信号处理帧周期长度不匹配，或者在整个信号处理帧周期的信噪比不一致，造成瞬时方位估计目标走向算法具有较大的误差，不利于目标参量估计与分类。采用Robust统计对瞬时方位估计数据进行处理，能够有效降低目标方位走向估计的误差。本文通过对Huber估计进行了分析并提出了改进Huber估计，给出了其工程实现算法，实验验证该Robust统计在降低目标方位走向估计误差上具有稳健收敛的性能。

Application of Robust statistics to target bearing estimation for split arrays in active SONAR

The normal mode (least square producers) loses efficiency drastically when the length of digital signal processing does not match the length of echo, or the SNR is not a constant in target bearing estimation. Indeed, a single outlier can have an arbitrarily large effect on the estimate. It causes significant errors in regression coefficients. This paper analyzes the reasons and gives a time-bearing model. Robust statistics and Huber-estimator are introduced. A modified Huber estimator presented and its application introduced. Simulation results show that the method can provide better and robust effect on bearing estimation..