Abstract
Micro-motion parameter estimation is a significant part in feature extraction of non cooperative targets, and precession is the common micro-motion form of space targets. However, most of the existing precession parameter estimation algorithms are based on pure precession condition assuming a constant nutation angle. Moreover, they do not consider the problems caused by nutation, such as a worse estimation accuracy, difficulties in estimating some parameters, and ambiguous frequency judgment. At the same time, the echoes from different scattering attribute components of the actual target also challenge the applicability of the existing algorithms. Therefore, this article proposes a robust and unambiguous algorithm for multidimensional parameter estimation. First, according to the modulation characteristics of micro-motion, the echoes from different scattering attribute components of the target are identified and separated for the applicability of the estimation algorithm. Second, considering the model of range variation curve, a robust way for precession parameter estimation is proposed to avoid worse accuracy and difficult estimation. Third, unambiguous judgment criteria are established by analyzing frequency spectrum distribution. Finally, multidimensional parameter estimation is realized, including motion feature and structure feature of the target. The proposed algorithm is also verified by electromagnetic analysis data.
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More From: IEEE Transactions on Geoscience and Remote Sensing
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