舰船科学技术2024,Vol.46Issue(6) :131-134.DOI:10.3404/j.issn.1672-7649.2024.06.022

基于海试数据的水声信号自适应波束形成方法性能分析

Performance analysis of adaptive beamforming method for underwater acoustic signals based on sea trial data

李智忠 徐仲恩 郭启超
舰船科学技术2024,Vol.46Issue(6) :131-134.DOI:10.3404/j.issn.1672-7649.2024.06.022

基于海试数据的水声信号自适应波束形成方法性能分析

Performance analysis of adaptive beamforming method for underwater acoustic signals based on sea trial data

李智忠 1徐仲恩 1郭启超1
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作者信息

  • 1. 海军潜艇学院,山东青岛 266199
  • 折叠

摘要

为了更好验证自适应波束形成技术的实际应用,本文研究了基于海试数据的不同自适应波束形成方法的性能,对比分析CBF算法、MVDR算法、MUSIC算法的优缺点,总结了各算法适用条件及实用性.研究结果表明,在声呐的实际应用中,CBF算法更适用于实时性要求较高、目标数量较少的方位探测;MUSIC算法更适用于实时性要求不高、目标数量较多、目标数量已知的方位探测;MVDR算法更适用于实时性要求不高、目标数量较多、目标数量未知的方位探测.

Abstract

To better verify the practical application of adaptive beamforming technology,this paper studies the per-formance of different adaptive beamforming methods based on sea trial data,compares and analyzes the advantages and dis-advantages of the CBF algorithm,MVDR algorithm,and MUSIC algorithm,and summarizes the applicability conditions and practicality of each algorithm.The results show that,in the practical application of sonar,the CBF algorithm is more suitable for bearing detection with high real-time requirements and a small number of targets;the MUSIC algorithm is more suitable for bearing detection with a low real-time requirement,a large number of targets and known number of targets;the MVDR algorithm is more suitable for bearing detection with a low real-time requirement,a large number of targets and the unknown number of targets.

关键词

自适应波束形成/MUSIC算法/MVDR算法/海试数据

Key words

adaptive beamforming/MUSIC algorithm/MVDR algorithm/sea trial data

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出版年

2024
舰船科学技术
中国舰船研究院,中国船舶信息中心

舰船科学技术

CSTPCD北大核心
影响因子:0.373
ISSN:1672-7649
参考文献量10
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