3D reconstruction of high‐speed moving targets based on HRR measurements. Issue 5 (1st May 2017)

• Record Type: Journal Article
• Authors: Yanxian, Bi; Shaoming, Wei; Jun, Wang
• Is Part Of: IET radar, sonar & navigation. Volume 11:Issue 5(2017)
• Page Start: 778
• Page End: 787
• Publication Date: 2017-05-01
• Subjects: image motion analysis -- object detection -- radar detection -- image reconstruction -- singular value decomposition -- spectral analysis -- feature extraction -- radar resolution -- image resolution -- scattering -- radar imaging -- synthetic aperture radar; high‐speed moving target reconstruction -- HRR measurements -- three‐dimensional target reconstruction -- inverse synthetic aperture radar -- ISAR imaging -- target scattering modelling -- target detection -- target identification -- noncooperative manoeuvring targets -- 3D target geometry reconstruction -- high‐resolution range measurements -- target motion features -- translation compensation -- multiview HRR -- HR spectral estimation -- multiple hypotheses tracking algorithm -- singular value decomposition -- correlated HRR data matrix; Signal processing -- Periodicals; Radar -- Periodicals; Sonar -- Periodicals; Electronics in navigation -- Periodicals; Navigation -- Periodicals; 621.3848
• DOI: 10.1049/iet-rsn.2016.0426
• Languages: English
• ISSNs: 1751-8784

Abstract

Abstract : Three‐dimensional (3D) target reconstruction from inverse synthetic aperture radar (ISAR) data has a wide application in target scattering modelling, detection, and identification. In ISAR imaging of targets with complex motions such as the non‐cooperative manoeuvring targets, the scattering centres on the target may rotate slowly in 3D space during the observation time. In this study, the authors have developed a new formulation for 3D target geometry reconstruction from the scattering centres high‐resolution range (HRR) measurements, based on target motion features. First, after the translation compensation, the multi‐view HRR of the scattering centres is extracted by HR spectral estimation technique. Then, the multi‐view measurements data without correspondence information are associated using the multiple hypotheses tracking algorithm. Finally, the 3D target geometry and motion are reconstructed from the singular value decomposition of the correlated HRR data matrix. The effectiveness of the proposed algorithm is demonstrated by both simulated and real data experiment results.