A Feature-Level Fusion-Based Target Localization Method with the Hough Transform for Spatial Feature Extraction
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Published:2023-04-17
Issue:8
Volume:15
Page:2121
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ISSN:2072-4292
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Container-title:Remote Sensing
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language:en
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Short-container-title:Remote Sensing
Author:
Wang Lu1, Fang Shiliang1, Yang Yixin2, Liu Xionghou2, Wang Mengyuan3
Affiliation:
1. Key Laboratory of Underwater Acoustic Signal Processing of Ministry of Education, Southeast University, Nanjing 210096, China 2. School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, China 3. State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
Abstract
Traditional two-step localization methods and direct localization methods have practical problems when they are used for underwater acoustic source localization. In this paper, a localization method based on the feature-level information fusion is proposed, in which the Hough Transform is exploited to detect the line characteristics of the spatial features of the target. A secondary accumulation procedure is proposed to extract and fuse the good features instead of fusing all features. The possibility to produce a ghost target is greatly reduced. Hence, the robustness of the proposed method in low SNR scenarios is improved. Experimental results validate the efficiency of exploiting the Hough Transform to eliminate interfering spatial features without sacrificing the localization accuracy.
Funder
National Natural Science Foundation of China State Key Laboratory of Acoustics, Chinese Academy of Sciences Fundamental Research Funds for the Central Universities
Subject
General Earth and Planetary Sciences
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