Weighted least-squares estimation of phase errors for SAR/ISAR autofocus
作者： Wei Ye , Tat Soon Yeo , Zheng Bao
DOI: 10.1109/36.789644
关键词:
摘要: A new method of phase error estimation that utilizes the weighted least-squares (WLS) algorithm is presented for synthetic aperture radar (SAR)/inverse SAR (ISAR) autofocus applications. The does not require signal in each range bin be a certain distribution model, and thus it robust many kinds scene content. most attractive attribute can used to estimate all errors, no matter whether they are low order, high or random. Compared with other methods, WLS optimal sense has minimum variance error. Excellent results have been obtained autofocusing imaging experiments on real ISAR data.
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