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

• المؤلفون الرئيسيون: Yang, Lei, Zhao, Lifan, Bi, Guoan, Zhang, Liren
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2017
• الموضوعات: Ground moving target imaging; Lv’s distribution
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/86047; http://hdl.handle.net/10220/43922
• المؤسسة: 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...