SAR Ground Moving Target Imaging Algorithm Based on Parametric and Dynamic Sparse Bayesian Learning

• Main Authors: Yang, Lei, Zhao, Lifan, Bi, Guoan, Zhang, Liren
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2017
• Subjects: Ground moving target imaging; Lv’s distribution
• Online Access: https://hdl.handle.net/10356/86047; http://hdl.handle.net/10220/43922
• Institution: Nanyang Technological University

In this paper, a novel synthetic aperture radar (SAR) ground moving target imaging (GMTIm) algorithm is presented within a parametric and dynamic sparse Bayesian learning (SBL) framework. A new time-frequency representation, which is known as Lv's distribution (LVD), is employed on the moving t...