Abstract
Due to the large size of space targets, migration through resolution cells (MTRC) are induced by a rotational motion in high-resolution bistatic inverse synthetic aperture radar (Bi-ISAR) systems. The inaccurate correction of MTRC degrades the quality of Bi-ISAR images. However, it is challenging to correct the MTRC where sparse aperture data exists for Bi-ISAR systems. A joint approach of MTRC correction and sparse high-resolution imaging for Bi-ISAR systems is presented in this paper. First, a Bi-ISAR imaging sparse model-related to MTRC is established based on compress sensing (CS). Second, the target image elements and noise are modeled as the complex Laplace prior, and the Gaussian prior, respectively. Finally, the high-resolution, well-focused image is obtained by the full Bayesian inference method, without manual adjustments of unknown parameters. Simulated results verify the effectiveness and robustness of the proposed algorithm.
Highlights
In monostatic ISAR imagery, the monstateic ISAR image cannot be attained when targets move along the line-of-sight (LOS) of the radar in the coherent processing interval (CPI)
The effectiveness and robustness of the proposed algorithm is verified by simulation results, and thethe proposed algorithm verified by simulation results, based effectiveness androbustness robustness of algorithm is verified by point simulation basedThe on effectiveness dataset of scatterer models ofofboth an proposed ideal point and aniselectromagnetic in this results, section
The proposed algorithm can obtain clear images in the four different cases, even with few pulses, as the sparsity of the image is reduced without considering the migration through resolution cells (MTRC) correction in [23]
Summary
In monostatic ISAR imagery, the monstateic ISAR image cannot be attained when targets move along the line-of-sight (LOS) of the radar in the coherent processing interval (CPI). In [23], we proposed a Bi-ISAR sparse imaging algorithm, based on Bayesian sparse reconstruction, with Laplace prior. In [4], a reconstruction method, based on l1 -norm, is used to achieve the MTRC correction and ISAR imaging in monostatic ISAR systems. Further considerations on the joint approach of MTRC correction and high-resolution imaging need to be studied in Bi-ISAR systems with sparse apertures. We propose a Bi-ISAR sparse high-resolution imaging algorithm of the joint approach of the image reconstruction and MTRC correction. The reconstruction algorithm with full Bayesian inference utilizes the statistical posterior information, and avoids structural errors and a local minimum.
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