دورية أكاديمية

A Feature-Level Fusion-Based Target Localization Method with the Hough Transform for Spatial Feature Extraction

التفاصيل البيبلوغرافية
العنوان: A Feature-Level Fusion-Based Target Localization Method with the Hough Transform for Spatial Feature Extraction
المؤلفون: Lu Wang, Shiliang Fang, Yixin Yang, Xionghou Liu, Mengyuan Wang
المصدر: Remote Sensing, Vol 15, Iss 8, p 2121 (2023)
بيانات النشر: MDPI AG, 2023.
سنة النشر: 2023
المجموعة: LCC:Science
مصطلحات موضوعية: source localization, multiple arrays, hough transform, feature extraction, Science
الوصف: 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.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 15082121
2072-4292
Relation: https://www.mdpi.com/2072-4292/15/8/2121; https://doaj.org/toc/2072-4292
DOI: 10.3390/rs15082121
URL الوصول: https://doaj.org/article/18bd124f003743a5b84972f828ffb697
رقم الأكسشن: edsdoj.18bd124f003743a5b84972f828ffb697
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:15082121
20724292
DOI:10.3390/rs15082121