Deconvolution of mode composition beamforming for rotating source localization

Q3 Earth and Planetary Sciences
Ce Zhang, Wei Ma
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引用次数: 0

Abstract

Mode composition beamforming (MCB) is a frequency-domain rotating beamforming method for rotating acoustic source localization. Compared with other rotating beamforming methods, MCB has both wide applicability and high computational efficiency. The expression for MCB in literature is however not suitable for the application of deconvolution algorithms, which limits further improvements of dynamic range and spatial resolution of MCB. In this work, application of deconvolution algorithms to MCB is investigated. Firstly, the expression of MCB is transformed into a matrix form. Then the deconvolution algorithms of MCB, including DAMAS and CLEAN-SC, are derived based on the matrix form of MCB. Nextly the deconvolution algorithms of MCB are verified through a benchmark simulation case. Lastly deconvolution algorithms of MCB are applied in a phased array measurement for the rotor of an unmanned aerial vehicle to improve the dynamic range and spatial resolution of rotating source localization.

用于旋转源定位的模式组成波束成形解卷积
模式构成波束成形(MCB)是一种用于旋转声源定位的频域旋转波束成形方法。与其他旋转波束成形方法相比,MCB 不仅适用范围广,而且计算效率高。然而,文献中的 MCB 表达式并不适合去卷积算法的应用,这限制了 MCB 动态范围和空间分辨率的进一步提高。在这项工作中,研究了去卷积算法在 MCB 中的应用。首先,将 MCB 的表达式转换为矩阵形式。然后,根据 MCB 的矩阵形式推导出 MCB 的解卷积算法,包括 DAMAS 和 CLEAN-SC。然后,通过基准模拟案例验证 MCB 的解卷积算法。最后,将 MCB 的解卷积算法应用于无人机转子的相控阵测量,以提高旋转源定位的动态范围和空间分辨率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Aerospace Systems
Aerospace Systems Social Sciences-Social Sciences (miscellaneous)
CiteScore
1.80
自引率
0.00%
发文量
53
期刊介绍: Aerospace Systems provides an international, peer-reviewed forum which focuses on system-level research and development regarding aeronautics and astronautics. The journal emphasizes the unique role and increasing importance of informatics on aerospace. It fills a gap in current publishing coverage from outer space vehicles to atmospheric vehicles by highlighting interdisciplinary science, technology and engineering. Potential topics include, but are not limited to: Trans-space vehicle systems design and integration Air vehicle systems Space vehicle systems Near-space vehicle systems Aerospace robotics and unmanned system Communication, navigation and surveillance Aerodynamics and aircraft design Dynamics and control Aerospace propulsion Avionics system Opto-electronic system Air traffic management Earth observation Deep space exploration Bionic micro-aircraft/spacecraft Intelligent sensing and Information fusion
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