Abstract
Feature extraction is a crucial step in synthetic aperture radar (SAR) automatic target recognition (ATR). This paper proposes a new feature extraction algorithm named optimal multiple kernel local discriminant embedding (OMKLDE). Based on kernel local discriminant embedding (KLDE), OMKLDE introduces multiple kernel functions and constructs an optimal model. Under this model, we use optimal method to obtain the expected mapping, which enhances interclass separability and maintains intraclass compactness, and more important, solves the parameter selecting problem in kernel trick. Experimental results based on MSTAR database show that the proposed method improves the stability and accuracy of recognition effectively.
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