A bistatic inverse synthetic aperture radar sparse aperture high‐resolution imaging algorithm with migration compensation
In recent years, bistatic inverse synthetic aperture radar (Bi‐ISAR) imaging of targets with sparse aperture has attracted more and more attention. One of the critical issues is that the Bi‐ISAR imaging of some large targets with rotational motions is prone to migration through resolution cells, whi...
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| Published in | IET radar, sonar & navigation Vol. 16; no. 12; pp. 1949 - 1962 |
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01.12.2022
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| Abstract | In recent years, bistatic inverse synthetic aperture radar (Bi‐ISAR) imaging of targets with sparse aperture has attracted more and more attention. One of the critical issues is that the Bi‐ISAR imaging of some large targets with rotational motions is prone to migration through resolution cells, which increases the imaging difficulty. In order to enhance the compensation for through resolution cell migration in those scenarios and improve the accuracy and resolution of Bi‐ISAR images under sparse aperture, that is, improving the target recognition of Bi‐ISAR, the authors aimed at the high‐order migration term and the high‐order phase error term and proposed a Bi‐ISAR sparse aperture high‐resolution imaging algorithm based on complex Bayesian compressed sensing and frequency resampling. The algorithm was solved by ‘distributed’ iteration. The migration compensation under the sparse aperture conditions was completed, and the quality of the reconstructed images was improved. Simulation results verified the effectiveness and superiority of the proposed algorithm. |
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| AbstractList | In recent years, bistatic inverse synthetic aperture radar (Bi‐ISAR) imaging of targets with sparse aperture has attracted more and more attention. One of the critical issues is that the Bi‐ISAR imaging of some large targets with rotational motions is prone to migration through resolution cells, which increases the imaging difficulty. In order to enhance the compensation for through resolution cell migration in those scenarios and improve the accuracy and resolution of Bi‐ISAR images under sparse aperture, that is, improving the target recognition of Bi‐ISAR, the authors aimed at the high‐order migration term and the high‐order phase error term and proposed a Bi‐ISAR sparse aperture high‐resolution imaging algorithm based on complex Bayesian compressed sensing and frequency resampling. The algorithm was solved by ‘distributed’ iteration. The migration compensation under the sparse aperture conditions was completed, and the quality of the reconstructed images was improved. Simulation results verified the effectiveness and superiority of the proposed algorithm. Abstract In recent years, bistatic inverse synthetic aperture radar (Bi‐ISAR) imaging of targets with sparse aperture has attracted more and more attention. One of the critical issues is that the Bi‐ISAR imaging of some large targets with rotational motions is prone to migration through resolution cells, which increases the imaging difficulty. In order to enhance the compensation for through resolution cell migration in those scenarios and improve the accuracy and resolution of Bi‐ISAR images under sparse aperture, that is, improving the target recognition of Bi‐ISAR, the authors aimed at the high‐order migration term and the high‐order phase error term and proposed a Bi‐ISAR sparse aperture high‐resolution imaging algorithm based on complex Bayesian compressed sensing and frequency resampling. The algorithm was solved by ‘distributed’ iteration. The migration compensation under the sparse aperture conditions was completed, and the quality of the reconstructed images was improved. Simulation results verified the effectiveness and superiority of the proposed algorithm. |
| Author | Zhou, Bin Xue, Dongfang Zhu, Chang'an Hu, Wenhua Zhu, Hanshen Zhu, Xiaoxiu Guo, Baofeng |
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| Title | A bistatic inverse synthetic aperture radar sparse aperture high‐resolution imaging algorithm with migration compensation |
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