<title>Design for HMM-based SAR ATR</title>

This paper describes progress on the Automatic Target Recognition (ATR) system for Synthetic Aperture Radar (SAR) imagery. The system is based upon a feature extraction, data ordering, and statistical modeling paradigm. Feature extraction is performed by applying image segmentation to convert the SAR imagery into one of four pixel classes. A description of a real-time image segmentation design is given. The segmented imagery is re-ordered from a 2D spatial representation to a sequential representation through the use of multiple Radon Transforms. Finally, the re-ordered data is classified by target type by applying Hidden Markov Model decoding techniques. Performance results on the MSTAR public targets database is provided.