Linear-Array-MIMO SAR Tomography: An Autofocus Approach for Time-Variant and 3-D Space-Variant Motion Errors
| Autor: | Linghao Li, Tianyi Zhang, Minkun Liu, Wenbin Gao, Weiming Tian, Tao Zeng, Yan Wang, Zegang Ding |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | IEEE Transactions on Geoscience and Remote Sensing. 60:1-17 |
| ISSN: | 1558-0644 0196-2892 |
| DOI: | 10.1109/tgrs.2021.3102072 |
| Popis: | Linear-array multiple-input-multiple-output (LA-MIMO) synthetic aperture radar (SAR) can obtain 3-D radar images by only one pass. However, it is sensitive to time-variant measurement errors of curved track and time-variant attitude angles, meaning that autofocus processing for the LA-MIMO SAR tomography is necessary. The existing autofocus methods cannot be used to estimate the time-variant and 3-D space-variant motion errors (3-D SVME) of the LA-MIMO SAR. To solve this problem, a new autofocus approach based on multiple local autofocusing and the LA-MIMO SAR time-variant motion error estimation is proposed. First, the local motion error estimation based on the fast local spectral analysis (SPECAN) 3-D imaging and the maximum contrast optimization 2-D local autofocusing is performed to estimate the local time-variant motion errors. Then, based on the linear-array motion error model, the time-variant 3-D trajectory deviations of the array center and attitude angles are estimated by the weighted least square estimation (WLSE) to solve the 3-D SVMEs. Last, the 3-D fast factorized backprojection (FFBP) is performed to obtain the well-focused 3-D image of the whole beam. The proposed approach has been applied for the tomography of a new crawler-type unmanned-ground-vehicle (UGV) LA-MIMO SAR. Both the simulation and real data experiments verify the effectiveness of the proposed approach. |
| Databáze: | OpenAIRE |
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