一种基于降维多信号分类的密集阵列直接定位算法

IF 1.9 4区计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

International Journal of Distributed Sensor Networks Pub Date : 2022-05-01 DOI:10.1177/15501329221097583

Jianfeng Li, Gaofeng Zhao, Baobao Li, Xianpeng Wang, Mengxing Huang

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引用次数: 0

摘要

针对传统两步定位中的参数匹配问题，提出了一种基于多阵列的降维多信号分类直接定位算法。该算法基于降维思想，避免了空间域和衰减系数域的多维搜索，降低了搜索复杂度。仿真结果表明，该算法的性能优于传统的到达角两步定位算法和子空间数据融合直接定位算法。

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

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.

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来源期刊

International Journal of Distributed Sensor Networks 工程技术-电信学

CiteScore

6.50

自引率

4.30%

发文量

审稿时长

3.6 months

期刊介绍： International Journal of Distributed Sensor Networks (IJDSN) is a JCR ranked, peer-reviewed, open access journal that focuses on applied research and applications of sensor networks. The goal of this journal is to provide a forum for the publication of important research contributions in developing high performance computing solutions to problems arising from the complexities of these sensor network systems. Articles highlight advances in uses of sensor network systems for solving computational tasks in manufacturing, engineering and environmental systems.