A reduced dimension multiple signal classification-based direct location algorithm with dense arrays

被引：3

作者：

Li, Jianfeng ^{[1
,2
]}

Zhao, Gaofeng ^{[2
]}

Li, Baobao ^{[2
]}

Wang, Xianpeng ^{[1
]}

Huang, Mengxing ^{[1
]}

机构：

[1] Hainan Univ, State Key Lab Marine Resource Utilizat South Chin, Haikou, Hainan, Peoples R China

[2] Nanjing Univ Aeronaut & Astronaut, Coll Elect Informat Engn, Nanjing 211106, Peoples R China

来源：

INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS | 2022年 / 18卷 / 05期

基金：

中国博士后科学基金;

关键词：

Direct position determination; multi-array; passive localization; DIRECT POSITION DETERMINATION; DOA ESTIMATION; MIMO RADAR; LOCALIZATION;

D O I：

10.1177/15501329221097583

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Aiming at the issue of parameter matching in conventional two-step location, a reduced dimension multiple signal classification direct position determination algorithm based on multi-array is proposed. Based on the idea of dimension reduction, the algorithm avoids multi-dimensional search in spatial domain and attenuation coefficient domain and reduces the search complexity. Simulation results show that the performance of the algorithm is better than the traditional angle of arrival two-step localization algorithm and subspace data fusion direct localization algorithm.

引用

页数：8

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