基于扇区特征向量约束的稳健自适应匹配场处理器

Robust adaptive matched field processing with sector eigenvector constraints

自适应匹配场处理可以获得较高的定位精度和旁瓣抑制性能,但需要精确计算的拷贝场向量和参数搜索空间内的精细采样,这为自适应匹配场在实际复杂海洋环境中的实时应用造成了困难。本文提出了一种新的稳健自适应匹配场处理算法,用以同时克服环境参数失配和实时搜索计算量大这两个问题。新算法集成了邻点位置约束、环境扰动约束和扇区聚焦约束等三种自适应匹配场处理器的优点,采用扇区与环境扰动双重约束,不仅对环境参数失配更具宽容性,而且可确保目标位于扇区内的任何点时,主瓣增益损失较小。典型浅海环境下的数值仿真和实测数据分析表明,该算法在一定的环境失配条件下不仅能有效地检测定位目标,还能实现距离/深度平面内的大扇区目标搜索,可大大减小实时运算量。

Standard adaptive beamforming or matched field processing requires accurate replica fields finely gridded over the search parameter space for localization with sidelobe control. This paper presents a new adaptive matched field processing （AMFP） algorithm, which aims at gaining robustness for the environmental mismatch, and simultaneously reducing the reM-time computational load. The new method integrates the merits of several AMFP beamformers with neighboring location constraints, environmental perturbation constraints and sector focusing constraints. The robustness and effectiveness of the suggested algorithm has been illustrated through the numerical simulation and the experimental Mediterranean benchmark shallow-water data.