A new algorithm for pose estimation of vehicles in SAR imagery is presented. Using robust features and a structured decision process, the algorithm achieves high precision. Four neural networks are used to make estimates conditional on angular regions, and another neural network is used to fuse these estimates. For the MSTAR Test Sample, the absolute error has a mean of 2 degrees with a standard deviation of 2.1, which is significantly more precise than previously reported results.
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