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High-Resolution Bistatic ISAR Imaging Based on Two-Dimensional Compressed Sensing.
- Source :
-
IEEE Transactions on Antennas & Propagation . May2015, Vol. 63 Issue 5, p2098-2111. 14p. - Publication Year :
- 2015
-
Abstract
- The theory of compressed sensing (CS) states that an unknown sparse signal can be accurately recovered from a limited number of measurements by solving a sparsity-constrained optimization problem. In this paper, we present a new framework of high-resolution bistatic inverse synthetic aperture radar (Bi-ISAR) imaging based on CS. A phase-preserved CS approach for high-range resolution imaging is proposed. The phase of a Bi-ISAR signal can be extracted by constructing a phase-preserved Fourier basis, which is crucial to azimuth processing of Bi-ISAR imaging. After performing CS reconstruction in range, we present an improved version of CS-based cross-range imaging by combining modified Fourier basis and weighting with CS optimization. Simulated data are used to test the robustness of the Bi-ISAR imaging framework with two-dimensional (2-D) CS method. The results show that the framework is capable of accurate reconstruction of Bi-ISAR image in both range and cross-range. [ABSTRACT FROM PUBLISHER]
Details
- Language :
- English
- ISSN :
- 0018926X
- Volume :
- 63
- Issue :
- 5
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Antennas & Propagation
- Publication Type :
- Academic Journal
- Accession number :
- 102497746
- Full Text :
- https://doi.org/10.1109/TAP.2015.2408337