Off-grid sparse ISAR imaging by Hlog-DCD algorithm

Author

Tianyun Wang ; Xinfei Lu ; Zhendong Xi ; Zhiqiang Song ; Haiming Tong ; Weidong Chen

Author_Institution

Key Lab. of Electromagn. Space Inf., Univ. of Sci. & Technol. of China, Hefei, China

fYear

2014

Firstpage

1

Lastpage

4

Abstract

In this paper, a novel computationally efficient algorithm is proposed to achieve high resolution for inverse synthetic aperture radar (ISAR) imaging in the compressive sensing (CS) framework, which is based on dichotomous coordinate descent (DCD) iterations, homotopy, and non-convex regularization. Since traditional CS based methods have to assume that unknown scatterers exactly lie on the pre-discretized grids, otherwise their inversion performance would degrade considerably. Herein we present Hlog-DCD algorithm combined with grid refinement technique to provide performance improvement of the image reconstruction for off-grid target. Experimental results verify the effectiveness of the proposed approach and related analysis.

Keywords

compressed sensing; image reconstruction; radar imaging; synthetic aperture radar; CS based methods; Hlog-DCD algorithm; compressive sensing framework; dichotomous coordinate descent iterations; homotopy; image reconstruction; inverse synthetic aperture radar imaging; inversion performance; nonconvex regularization; off-grid sparse ISAR imaging; off-grid target; prediscretized grids; Image reconstruction; Image resolution; Imaging; Radar imaging; Sparse matrices; Vectors; Hlog-DCD algorithm; ISAR imaging; grid refinement technique; off-grid target; sparse reconstruction;

fLanguage

English

Publisher

ieee

Conference_Titel

Radar Conference (Radar), 2014 International

Type

conf

DOI

10.1109/RADAR.2014.7060461

Filename

7060461