Analysis of Direction-Finding Performance of Vector Hydrophones Based on Unmanned Underwater Vehicle Platforms and Application Research of Embodied Cognition Theory

基于无人水下航行器平台的矢量水听器测向性能分析及具身认知理论的应用研究

阅读:1

Abstract

To address the problem of platform scattering interference in direction finding using vector hydrophones mounted on unmanned underwater vehicle (UUV) platforms, this paper introduces a direction-finding error compensation method based on embodied transfer function (ETF) correction within the framework of embodied cognition theory. By establishing an analytical model of the scattered sound field of an infinite rigid cylinder, the influence mechanism of the UUV platform on the sound pressure and vibration velocity measurements of the vector hydrophone is systematically investigated, and the concepts of sound pressure ETF and vibration velocity ETF are defined. The research results indicate that at an operating frequency of 800 Hz, the ETF-based direction-finding method reduces the average direction-finding error from 8.8° to 6.2°, representing a performance improvement of 30.2%. Moreover, when the target lies near the transverse, the direction-finding error of the embodied model remains below 1.5°. This study provides novel theoretical support and a technical framework for achieving high-precision direction finding of vector hydrophones mounted on UUV platforms.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。