ISAR Imaging Based on Sparse Signal Representation with Multiple Measurement Vectors

Author

Cheng, Ping ; Jiang, Yicheng ; Xu, Rongqing

Author_Institution

Res. Inst. of Electron. Eng. Technol., Harbin Inst. of Technol.

fYear

2006

fDate

16-19 Oct. 2006

Firstpage

1

Lastpage

4

Abstract

A new imaging method is proposed for ISAR with multiple measurement vectors (MMV) based on sparse signal representation. As an extension of single measurement sparse signal representation, MMV can enhance the ability of suboptimal procedure to find the proper sparse solution and also offers potential robustness to noise, supposing the measurement vectors having a same sparsity structure. Simulations have shown its superior performance. Here it is first presented for ISAR imaging. Imaging result of real data shows it is a promising method for ISAR

Keywords

image representation; radar imaging; synthetic aperture radar; ISAR imaging; MMV; inverse synthetic aperture radar; multiple measurement vector; sparse signal representation; Cost function; Dictionaries; Focusing; Matching pursuit algorithms; Noise measurement; Noise robustness; Pursuit algorithms; Sensor arrays; Signal representations; Wavelet packets; FOCUSS; ISAR; MMV (Multiple Measurement Vectors); sparse signal representation;

fLanguage

English

Publisher

ieee

Conference_Titel

Radar, 2006. CIE '06. International Conference on

Conference_Location

Shanghai

Print_ISBN

0-7803-9582-4

Electronic_ISBN

0-7803-9583-2

Type

conf

DOI

10.1109/ICR.2006.343425

Filename

4148462