MICROWAVE STARING CORRELATED IMAGING BASED ON QUASI-STATIONARY PLATFORM WITH MOTION MEASUREMENT ERRORS
Microwave staring correlated imaging (MSCI) is a promising technique for remote sensing due to its ability to achieve high-resolution microwave imaging without the limitation of relative motion between target and radar. In practical applications, unsteady quasi-stationary platforms, such as tethered...
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Veröffentlicht in: | Progress in electromagnetics research M Pier M 2020-01, Vol.97, p.1-12 |
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Zusammenfassung: | Microwave staring correlated imaging (MSCI) is a promising technique for remote sensing due to its ability to achieve high-resolution microwave imaging without the limitation of relative motion between target and radar. In practical applications, unsteady quasi-stationary platforms, such as tethered aerostat, are often used as carriers of MSCI radar. However, these platforms cannot keep ideally stationary during the imaging process. The platform's motion caused by atmospheric effects will cause time-varying inaccuracy of observation positions. Although navigation systems can measure the platform's motion to compensate for the errors of observation positions, the imaging performance of MSCI may still suffer from degradation due to the measurement errors of navigation systems since MSCI is sensitive to model error. This paper focuses on MSCI based on the quasi-stationary platform with motion measurement errors. First, the MSCI model based on the quasi-stationary platform with motion measurement errors is established under the assumption that the translation and the rotation of the platform are uniform during a coherent imaging interval. Then we propose a self-calibration imaging method for MSCI based on the quasi-stationary platform with motion measurement errors. This method iterates over the steps of target reconstruction and motion measurement errors correction until convergent conditions are met. Simulation results show that the proposed method can correct the motion measurement errors and improve imaging performance significantly. |
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ISSN: | 1937-8726 1937-8726 |
DOI: | 10.2528/PIERM20061802 |