【摘要】 针对浅海中由于水声环境参数不确定、水面强干扰的存在、以及目标运动等因素会导致水下弱目标检测与定位性能严重下降的问题,将协方差矩阵降阶、环境宽容性约束和运动补偿进行有机结合,在对运动补偿算法加以改进的基础上,提出了一种在不确定环境和强干扰背景下检测水下微弱目标的稳健自适应匹配场处理方案。典型浅海环境下的数值仿真和实测数据分析表明,该方案在一定的环境失配条件下不仅能有效地抑制水面强干扰,还能为水下微弱运动目标的检测提供较大范围的空时相干累积,有利于提高目标的定位精度和输出信干比。更多还原

【Abstract】 The main challenges on detection and localization of quiet targets in littoral regions for passive sonar are the complicated acoustic propagation and the prevalence of loud ship interference on the surface. Adaptive Matched Field Processing (AMFP) can provide the ability to null surface interference, but the mismatch between the computed and actual array steering vectors due to environment uncertainty, and the motion of both target and interference can result in loss of array gain significantly. To address the problem of environmental mismatch and target motion, a robust motion compensation algorithm and a system scheme for adaptive matched field processing have been developed. Both numerical simulation and analysis of experimental data demonstrated that the rpbust AMFP scheme could suppress surface loud interference and improve the detection performance for underwater weak moving target in complex shallow water.更多还原