浅水环境中基于ISODATA的多目标定位  

Localization of multiple targets based on ISODATA in shallow water

作　　者：王卓越 李宇[1,2,3] 王宇杰[1,2,3] 王硕 WANG Zhuoyue;LI Yu;WANG Yujie;WANG Shuo(Institute of Acoustic,Chinese Academy of Sciences,Beijing 100190,China;Key Laboratory of Science and Technology on Advanced Underwater Acoustic Signal Processing,Chinese Academy of Sciences,Beijing100190,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院声学研究所,北京100190 [2]中国科学院先进水下信息技术重点实验室,北京100190 [3]中国科学院大学,北京100049

出　　处：《声学技术》2023年第3期281-289,共9页Technical Acoustics

基　　金：国家自然科学基金(6200011928)。

摘　　要：由于不同距离目标到接收阵之间的格林函数图像存在的明显差异性,利用其特征进行分类可以实现对不同距离目标格林函数图像的区分。文章将聚类分析算法中的迭代自组织数据分析算法(Iterative Selforganizing Data Analysis Techniques Algorithm,ISODATA)应用到传统多目标定位过程中,经过连续干扰消除过程(Successive Interference Cancellation,SIC)的反复迭代,对提取出的多个格林函数进行分类。为解决传统多目标定位过程中需要人工判断格林函数异同的问题提供了一种可行途径,并进一步将分类出的格林函数通过阵不变量方法解算出不同目标的距离信息。In view of the obvious difference of Green's function in different distances,the targets at different distances can be distinguished by classification according to their characteristics.In this paper,the iterative selforganizing data analysis techniques algorithm(ISODATA)clustering algorithm is applied to the traditional multi-objective successive interference cancellation(SIC)process in multi-target positioning,and the Green's functions extracted from the SIC process are classified after repeated iteration.Therefore,the problem that the similarities and differences of Green's functions need to be judged manually in the traditional multi-target positioning process is solved,and the distance information of different targets is further calculated by using the classified Green's functions.

关 键 词：阵不变量 多目标定位 被动定位 聚类分析 

分 类 号：O427[理学—声学]