非平稳异质噪声水下无人平台目标稳健探测

Underwater Unmanned Platform Target Robust Detection in Non-Stationary Heteroscedastic Noise Environment

摘要:

水下无人集群平台搭载主动声呐在关键海域开展水下目标探测,是探测“安静型”目标的首选手段。但海洋环境噪声往往呈现典型的非平稳、异方差及强脉冲特性,令传统基于高斯噪声假设的参数估计方法性能下降。本文提出一种基于加权迭代Lq范数稀疏重构的目标回波时延估计方法,通过构建Lq(0

Abstract:

Employing underwater unmanned vehicle swarms equipped with active sonar to detect underwater targets in key maritime areas has become the preferred approach for locating “quiet” targets. However, ocean ambient noise often exhibits typical non?stationary, heteroscedastic, and impulsive characteristics, which degrade the performance of traditional parameter estimation methods based on Gaussian noise assumptions. To address this issue, this paper proposes a robust time-delay estimation method for target echoes based on weighted iterative sparse reconstruction with an Lq-norm constraint. By employing an Lq-norm loss function (0