Abstract: We present a low-complexity model-based FOPEN target detection algorithm and discuss its potential application as a target screener within an end-to-end FOPEN SAR automatic target detection system. The algorithm uses multiple discriminants extracted over a local sliding window followed by a multivariate discrimination rule to perform target screening at the pixel level. We present detection performance results obtained against FOPEN SAR imagery and show that the multidiscriminant approach achieves better detection performance than a model-template matched-filter detection algorithm.!10
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