{"title":"使用单矢量水听器的到达方向矢量信号重构稀疏和参数方法","authors":"Jiabin Guo","doi":"arxiv-2404.15160","DOIUrl":null,"url":null,"abstract":"This article discusses the application of single vector hydrophones in the\nfield of underwater acoustic signal processing for Direction Of Arrival (DOA)\nestimation. Addressing the limitations of traditional DOA estimation methods in\nmulti-source environments and under noise interference, this study introduces a\nVector Signal Reconstruction Sparse and Parametric Approach (VSRSPA). This\nmethod involves reconstructing the signal model of a single vector hydrophone,\nconverting its covariance matrix into a Toeplitz structure suitable for the\nSparse and Parametric Approach (SPA) algorithm. The process then optimizes it\nusing the SPA algorithm to achieve more accurate DOA estimation. Through\ndetailed simulation analysis, this research has confirmed the performance of\nthe proposed algorithm in single and dual-target DOA estimation scenarios,\nespecially under various signal-to-noise ratio(SNR) conditions. The simulation\nresults show that, compared to traditional DOA estimation methods, this\nalgorithm has significant advantages in estimation accuracy and resolution,\nparticularly in multi-source signals and low SNR environments. The contribution\nof this study lies in providing an effective new method for DOA estimation with\nsingle vector hydrophones in complex environments, introducing new research\ndirections and solutions in the field of vector hydrophone signal processing.","PeriodicalId":501178,"journal":{"name":"arXiv - CS - Sound","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Vector Signal Reconstruction Sparse and Parametric Approach of direction of arrival Using Single Vector Hydrophone\",\"authors\":\"Jiabin Guo\",\"doi\":\"arxiv-2404.15160\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article discusses the application of single vector hydrophones in the\\nfield of underwater acoustic signal processing for Direction Of Arrival (DOA)\\nestimation. Addressing the limitations of traditional DOA estimation methods in\\nmulti-source environments and under noise interference, this study introduces a\\nVector Signal Reconstruction Sparse and Parametric Approach (VSRSPA). This\\nmethod involves reconstructing the signal model of a single vector hydrophone,\\nconverting its covariance matrix into a Toeplitz structure suitable for the\\nSparse and Parametric Approach (SPA) algorithm. The process then optimizes it\\nusing the SPA algorithm to achieve more accurate DOA estimation. Through\\ndetailed simulation analysis, this research has confirmed the performance of\\nthe proposed algorithm in single and dual-target DOA estimation scenarios,\\nespecially under various signal-to-noise ratio(SNR) conditions. The simulation\\nresults show that, compared to traditional DOA estimation methods, this\\nalgorithm has significant advantages in estimation accuracy and resolution,\\nparticularly in multi-source signals and low SNR environments. The contribution\\nof this study lies in providing an effective new method for DOA estimation with\\nsingle vector hydrophones in complex environments, introducing new research\\ndirections and solutions in the field of vector hydrophone signal processing.\",\"PeriodicalId\":501178,\"journal\":{\"name\":\"arXiv - CS - Sound\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Sound\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2404.15160\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Sound","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2404.15160","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
本文讨论了单矢量水听器在水下声学信号处理领域中对到达方向(DOA)估计的应用。针对传统 DOA 估算方法在多声源环境和噪声干扰下的局限性,本研究引入了矢量信号稀疏和参数重构方法(VSRSPA)。该方法包括重建单个矢量水听器的信号模型,将其协方差矩阵转换为适合稀疏和参数方法(SPA)算法的托普利兹结构。然后利用 SPA 算法对其进行优化,以实现更精确的 DOA 估计。通过详细的仿真分析,本研究证实了所提算法在单目标和双目标 DOA 估计场景中的性能,尤其是在各种信噪比(SNR)条件下。仿真结果表明,与传统的 DOA 估计方法相比,该算法在估计精度和分辨率方面具有显著优势,尤其是在多源信号和低信噪比环境下。本研究的贡献在于为复杂环境下的单矢量水听器 DOA 估计提供了一种有效的新方法,为矢量水听器信号处理领域引入了新的研究方向和解决方案。
Vector Signal Reconstruction Sparse and Parametric Approach of direction of arrival Using Single Vector Hydrophone
This article discusses the application of single vector hydrophones in the
field of underwater acoustic signal processing for Direction Of Arrival (DOA)
estimation. Addressing the limitations of traditional DOA estimation methods in
multi-source environments and under noise interference, this study introduces a
Vector Signal Reconstruction Sparse and Parametric Approach (VSRSPA). This
method involves reconstructing the signal model of a single vector hydrophone,
converting its covariance matrix into a Toeplitz structure suitable for the
Sparse and Parametric Approach (SPA) algorithm. The process then optimizes it
using the SPA algorithm to achieve more accurate DOA estimation. Through
detailed simulation analysis, this research has confirmed the performance of
the proposed algorithm in single and dual-target DOA estimation scenarios,
especially under various signal-to-noise ratio(SNR) conditions. The simulation
results show that, compared to traditional DOA estimation methods, this
algorithm has significant advantages in estimation accuracy and resolution,
particularly in multi-source signals and low SNR environments. The contribution
of this study lies in providing an effective new method for DOA estimation with
single vector hydrophones in complex environments, introducing new research
directions and solutions in the field of vector hydrophone signal processing.