Robust统计在主动声纳分裂波束目标方位走向估计中的应用

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

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。

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.