Decision fusion based on physically relevant features for SAR ATR. Issue 4 (1st April 2017)

• Record Type: Journal Article
• Authors: Ding, Baiyuan; Wen, Gongjian; Ma, Conghui; Yang, Xiaoliang
• Is Part Of: IET radar, sonar & navigation. Volume 11:Issue 4(2017)
• Page Start: 682
• Page End: 690
• Publication Date: 2017-04-01
• Subjects: synthetic aperture radar -- radar target recognition -- radar computing -- inference mechanisms; physically relevant features -- SAR ATR -- multifeature decision fusion -- synthetic aperture radar -- automatic target recognition -- ATR -- feature database -- Dempster‐Shafer evidence theory -- target acquisition -- recognition database; Signal processing -- Periodicals; Radar -- Periodicals; Sonar -- Periodicals; Electronics in navigation -- Periodicals; Navigation -- Periodicals; 621.3848
• DOI: 10.1049/iet-rsn.2016.0357
• Languages: English
• ISSNs: 1751-8784

Abstract

Abstract : Multi‐feature decision fusion is a robust way to enhance the performance of synthetic aperture radar (SAR) automatic target recognition (ATR). This study fuses two physically relevant features namely attributed scattering centres and target contour for SAR ATR. The two features provide an intuitive and comprehensive description of targets which can not only promote the ATR performance but also benefit human interpretation. The two features complement each other with weak spatial correlation. Furthermore, both the features can be concisely represented by simple point pattern thus remarkably saving the memory of the feature database. Specific classifiers are designed for the two features whose outputs are fused by the Dempster–Shafer evidence theory to produce the final decision. Experiments based on the moving and stationary target acquisition and recognition database demonstrate the validity of the proposed method.