Using Subspace Pursuit Method For Radar Image Reconstruction

DOI

10.2991/meic-14.2014.172How to use a DOI?

Keywords

Compressive sensing; subspace pursuit method; back projection; radar imaging; sparse reconstruction

Abstract

A compressive sensing based method is proposed for reconstruction of radar image of 3-D geometry in this paper. Using the sparse property of the geometry, compressed sensing performs a low-dimensional, non-adaptive and linear projection to acquire an efficient representation of a compressible signal directly using just a few measurements. In order to characterize the problem sparsely, the delta function is used as the sparse basis function. When testing by the incident plane wave at several different frequency points over wide band, linear equations are constructed following the theory of compressed sensing to recover the range profile of radar image. Subspace pursuit (SP) method is applied to solve the linear equations and the results are used for traditional Back-Projection (BP) imaging method. The physical optics is used to compute the scattering which is considered as the input data for compressed sensing based construction. Numerical results of several geometries show our method is robust and accuracy for radar imaging with sub-sampled data.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yueyuan Zhang
PY  - 2014/11
DA  - 2014/11
TI  - Using Subspace Pursuit Method For Radar Image Reconstruction
BT  - Proceedings of the 2014 International Conference on Mechatronics, Electronic, Industrial and Control Engineering
PB  - Atlantis Press
SP  - 769
EP  - 772
SN  - 2352-5401
UR  - https://doi.org/10.2991/meic-14.2014.172
DO  - 10.2991/meic-14.2014.172
ID  - Zhang2014/11
ER  -