摘要
针对浅海隐蔽低耗平台对目标探测的需求,将贝叶斯估计理论应用于水声定位领域,建立以概率密度函数为声源状态描述的水声定位模型,克服浅海环境非稳定和声场模型失配问题;采用直方图滤波法求解贝叶斯滤波问题,解决声源状态后验概率估计过程中积分求解的问题;提出分级网格划分直方图滤波法,有效提高迭代算法的效率;SWellEx-96实测数据和仿真结果表明,在浅海环境条件下,深度200 m,距离10 km的范围内,深度定位精度达到35 m,距离定位精度达到0.69 km,算法效率可以提高N1/2倍。
In order to meet the needs of target detection in shallow water with concealed and low energy consumption platform, the Bayesian estimation theory was applied to underwater acoustic location. The underwater acoustic location model was established based on probability density function as the description of sound source state, so as to overcome the problems of unstable shallow water environment and mismatching of sound field model. Histogram filtering method is used to solve the integral solution in the process of posterior probability estimation of sound source state. The hierarchical grid histogram filtering method is proposed for the first time, which effectively improves the efficiency of histogram filtering iterative algorithm. The measured data and simulation results of SWelleX-96 show that the depth positioning accuracy can reach 35 m and the distance positioning accuracy can reach 0.69 km within the range of 200 m deep and 10 km long in shallow water environment, and the efficiency of the algorithm can be improved by N1/2times.
作者
石海杰
李京华
常虹
SHI Haijie;LI Jinghua;CHANG Hong(School of Electronics and Information,Northwestern Polytechnical University,Xi′an 710072,China;School of Information and Communication Engineering,North University of China,Taiyuan 030051,China;School of Communications and Information Engineering,Xi′an University of Posts&Telecommunications,Xi′an 710121,China)
出处
《西北工业大学学报》
EI
CAS
CSCD
北大核心
2022年第6期1278-1287,共10页
Journal of Northwestern Polytechnical University
基金
陕西省重点研发计划(2020GY-56)资助。
关键词
贝叶斯估计
分级网格划分直方图滤波
浅海
水声定位
单水听器
Bayes estimation
hierarchical grid histogram filtering
shallow water
underwater acoustic location
single hydrophone