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- Title
ISAR imaging using null space l<sub>t</sub> norm minimization.
- Authors
XU Chu; ZHU Dongqiang; WANG Ling; WANG Jie
- Abstract
Under the assumption that the target scene is sparse, the compressive sensing (Cs) imaging can use very few data to obtain good images with high contrast and no side-lobe interference as compared with the conventional range-Doppier imaging methods. In this paper, an inverse synthetic aperture radar (IsAR) Cs imaging method based on the minimization of the null-space l1 norm is proposed. The soluiion of the undetermined linear imaging system is decomposed into two parts the prelimenary value and the residual value First, the weighted lease square method is used to esiimate the preliminary value, which is used as the target image Then, the l1norm of the target scene reflectivity is introduced as an additional nonlinear measurement and used in the image reconstruction. Wtthin the Kalman filter framework, the residual value in the null space is estimated by minimizing the l1 norm of the target scene using the nonlinear pseudo-measurement. The IsAR real data processing verifies the effectiveness of the proposed method. The image quality obtained by the proposed method is better than that of the orthogonal marching pursuit algorithni (OMP) and the l1 norm minimization method. The imaging time is much less than the primal-dual l1 norm minimization method and comparable to OMP.
- Subjects
INVERSE synthetic aperture radar; IMAGE reconstruction; KALMAN filtering; ESTIMATES
- Publication
Systems Engineering & Electronics, 2020, Vol 42, Issue 2, p315
- ISSN
1001-506X
- Publication type
Article
- DOI
10.3969/j.issn.1001-506X.2020.02.09