摘要
水声被动目标定位在海洋资源勘探、水下探测、海上安全监测等任务中有着重要应用,是水声领域最重要的课题之一。已有的经典方法如匹配场处理和压缩匹配场处理等,能够在预先划分好的距离-深度网格点上进行源定位,但是实际情况中的目标源会偏离网格点,导致此类方法的性能下降;且在压缩匹配场处理中,离网格源可能导致多个稀疏解对应单个源,呈现出多峰值模糊问题。针对该问题,考虑到由于水下相邻位置处的信道冲激响应极为相似,本文基于任意离网格位置的信道冲激响应可被周围网格点处的拷贝场向量近似拟合这一特性,建立了一种面向水下目标定位的群稀疏信号模型,并提出了相应的离网格压缩匹配场处理方法,通过恢复的稀疏信号计算出网格点处的插值系数对离网格源进行高精度定位。实验表明,在双源定位任务中,离网格压缩匹配场处理的定位性能优于传统的匹配场处理和压缩匹配场处理方法。当网格的距离间隔为0.05 km、深度间隔为10 m时,在信噪比大于−5 dB的条件下,离网格压缩匹配场处理的双源平均测距误差与压缩匹配场处理相比降低了250 m以上。
Passive target localization in underwater acoustics plays a crucial role in tasks such as marine resource explora-tion,underwater detection,and maritime security monitoring.It stands as one of the most pivotal subjects within the under-water acoustics domain.Proposed methods such as conventional matched field processing(MFP)and compressive MFP(CMFP)can effectively localize sources at the pre-divided range-depth grids.However,deviations of actual target sources from these grid points lead to performance degradation in such methods.In addition,the off-grid source may lead to multiple sparse solutions corresponding to a single source in CMFP,resulting in multi-peak ambiguity.Addressing these challenges,considering that the channel impulse response(CIR)at adjacent underwater locations present significant similarities,this pa-per capitalizes on the property that the CIR at any off-grid location can be approximated by the replica vectors at neighboring grid points.Based on this property,we established a group sparse signal model oriented towards underwater target localiza-tion.Subsequently,a corresponding off-grid compressive matched field processing(OG-CMFP)method is proposed.This method leverages the recovered sparse signal to compute interpolation coefficients at grid points,enabling high-precision lo-calization of off-grid sources.Experimental results demonstrate that,OG-CMFP outperforms traditional MFP and CMFP tech-niques in a two-source localization task.With a range interval of 0.05 km and a depth interval of 10 m,under conditions of SNR greater than-5 dB,OG-CMFP achieves an average rMAE reduction of over 250 m compared to CMFP.
作者
兰旭辉
杨成竹
徐立军
LAN Xuhui;YANG Chengzhu;XU Lijun(School of Information and Electronics,Beijing Institute of Technology,Beijing 100081,China)
出处
《信号处理》
CSCD
北大核心
2023年第10期1784-1792,共9页
Journal of Signal Processing
基金
国家自然科学基金青年基金(62201046)
国家自然科学基金重大项目课题(62192711,62192712)
国家重点研发计划专项课题(2022YFC2808002)。
关键词
离网格
稀疏重构
匹配场处理
水下源定位
off-grid
sparse reconstruction
matched field processing
underwater source localization
