The estimation of a target aspect angle is an important research problem in synthetic aperture radar (SAR) target
recognition. Thus, this paper is undertaken to study the algorithm for the estimation of the aspect angle based on the
Moving and Stationary Target Acquisition and Recognition (MSTAR) data set. The study employs segmentation based
on the Markov Random Field (MRF) to separate the target, shadow, and background. It then proposes two divergence
indices, target divergence index (TDI) and joint divergence index (JDI) of target and shadow, to describe the distribution
of pixels in target and shadow. The content of the paper is as follows. The first part presents an analysis of the
relationship between aspect angle and two indices, and extracts the common features of the aspect angle and the two
indices. The second part analyzes the advantages and disadvantages of the three methods. The last part presents the
proposal for a combined algorithm for tank aspect angle estimation. The results show that the proposed algorithm is effective.
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