Sparse representation for the ISAR image reconstruction

Author

Mengqi Hu, The University of Texas Rio Grande Valley

Date of Award

8-2016

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Mathematics

First Advisor

Dr. Zhijun Qiao

Second Advisor

Dr. Bin Fu

Third Advisor

Dr. Jasang Yoon

Abstract

In this paper, a sparse representation for the data form a multi-input multi-output based inverse synthetic aperture radar (ISAR) system is derived for two dimensions. The proposed sparse representation motivates the use a of a Convex Optimization directly that recovers the image without the loss information of the image with far less samples that that is required by Nyquist–Shannon sampling theorem, which increases the efficiency and decrease the cost of calculation in radar imaging.

Comments

Copyright 2016 Mengqi Hu. All Rights Reserved.

https://www.proquest.com/dissertations-theses/sparse-representation-isar-image-reconstruction/docview/1849508226/se-2?accountid=7119

Recommended Citation

Hu, Mengqi, "Sparse representation for the ISAR image reconstruction" (2016). Theses and Dissertations. 46.
https://scholarworks.utrgv.edu/etd/46