Xin Zhu, Fangzheng Zhang, Jiayuan Kong, S. Pan, Yuewen Zhou, Guanqun Sun
{"title":"Azimuth Super-resolution Imaging using Photonics-based Inverse Synthetic Aperture Radar","authors":"Xin Zhu, Fangzheng Zhang, Jiayuan Kong, S. Pan, Yuewen Zhou, Guanqun Sun","doi":"10.1109/ICSPCC55723.2022.9984621","DOIUrl":null,"url":null,"abstract":"Photonics-based inverse synthetic aperture radars can enable wide operation bandwidth and high range resolution. To improve the azimuth resolution, a large coherent accumulation angle or a sufficient observation time duration is required, which is difficult to achieve in practical applications. To overcome the sparse aperture problem of a photonics-based ISAR, azimuth super-resolution imaging is demonstrated in this paper, in which the sparse representation method is applied to implement sparse azimuth data extrapolation or fusion. In the experiment, the photonics-based radar has a bandwidth of 8 GHz, and ISAR echoes from a full observation aperture are selected to imitate the short-aperture detection and sparse aperture detection, respectively. Performance of the sparse-representation-based azimuth super resolution imaging method is investigated. Experimental results show that the azimuth resolution of a photonics-based ISAR can be greatly improved to get well focused images in which small targets can be well distinguished.","PeriodicalId":346917,"journal":{"name":"2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)","volume":"61 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSPCC55723.2022.9984621","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Photonics-based inverse synthetic aperture radars can enable wide operation bandwidth and high range resolution. To improve the azimuth resolution, a large coherent accumulation angle or a sufficient observation time duration is required, which is difficult to achieve in practical applications. To overcome the sparse aperture problem of a photonics-based ISAR, azimuth super-resolution imaging is demonstrated in this paper, in which the sparse representation method is applied to implement sparse azimuth data extrapolation or fusion. In the experiment, the photonics-based radar has a bandwidth of 8 GHz, and ISAR echoes from a full observation aperture are selected to imitate the short-aperture detection and sparse aperture detection, respectively. Performance of the sparse-representation-based azimuth super resolution imaging method is investigated. Experimental results show that the azimuth resolution of a photonics-based ISAR can be greatly improved to get well focused images in which small targets can be well distinguished.