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智能海洋:多波束声纳的一种新的快速去卷积波束形成算法。

Smart Ocean: A New Fast Deconvolved Beamforming Algorithm for Multibeam Sonar.

机构信息

Acoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China.

Key Laboratory of Marine Information Acquisition and Security, Harbin Engineering University, Harbin 150001, China.

出版信息

Sensors (Basel). 2018 Nov 17;18(11):4013. doi: 10.3390/s18114013.

Abstract

A new fast deconvolved beamforming algorithm is proposed in this paper, and it can greatly reduce the computation complexity of the original Richardson⁻Lucy (R⁻L algorithm) deconvolution algorithm by utilizing the convolution theorem and the fast Fourier transform technique. This algorithm makes it possible for real-time high-resolution beamforming in a multibeam sonar system. This paper applies the new fast deconvolved beamforming algorithm to a high-frequency multibeam sonar system to obtain a high bearing resolution and low side lobe. In the sounding mode, it restrains the tunnel effect and makes the topographic survey more accurate. In the 2D acoustic image mode, it can obtain clear images, more details, and can better distinguish two close targets. Detailed implementation methods of the fast deconvolved beamforming are given, its computational complexity is analyzed, and its performance is evaluated with simulated and real data.

摘要

本文提出了一种新的快速去卷积波束形成算法,该算法利用卷积定理和快速傅里叶变换技术,大大降低了原始 Richardson-Lucy(R-L)去卷积算法的计算复杂度。该算法使得在多波束声纳系统中实现实时高分辨率波束形成成为可能。本文将新的快速去卷积波束形成算法应用于高频多波束声纳系统,以获得高方位分辨率和低旁瓣。在探测模式下,它抑制了隧道效应,使地形测量更加精确。在二维声纳图像模式下,它可以获得清晰的图像,更多的细节,并能更好地区分两个接近的目标。本文详细给出了快速去卷积波束形成的实现方法,分析了其计算复杂度,并通过模拟数据和真实数据对其性能进行了评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5fa0/6263529/397ec130c18b/sensors-18-04013-g001.jpg

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