3D scattering image reconstruction based on measurement optimization of a radar network. Issue 7 (2nd July 2020)

• Record Type: Journal Article
• Authors: Kang, Le; Luo, Ying; Zhang, Qun; Liu, Xiao-Wen; Liang, Bi-Shuai
• Is Part Of: Remote sensing letters. Volume 11:Issue 7(2020)
• Page Start: 697
• Page End: 706
• Publication Date: 2020-07-02
• Subjects: Remote sensing -- Periodicals; Remote sensing; Periodicals; 621.3678
• DOI: 10.1080/2150704X.2020.1757781
• Languages: English
• ISSNs: 2150-704X

Abstract

ABSTRACT: For radar network, each radar can obtain the two-dimensional (2D) inverse synthetic aperture radar (ISAR) image from the corresponding observation angle independently. Taking advantage of the multi-view observation via radar network and the projection relationship in ISAR imaging, the three-dimensional (3D) image of the target can be reconstructed by the inverse-projection principle. However, it is hard to reconstruct the scattering position and coefficient simultaneously, and the network optimization should be studied to improve the reconstruction performance. To solve these problems, a novel 3D scattering image reconstruction method is proposed in this paper. Firstly, the 3D reconstruction model is built as a compressed sensing (CS) framework. Then, the network optimization for single target is transformed into the measurement matrix optimization before the 3D scattering recovery. Finally, numerical simulations under the noise scenarios and the principle prototype experiment on real data are shown to demonstrate the validity of the proposed method.