An SAR ATR Method Based on Scattering Centre Feature and Bipartite Graph Matching

ABSTRACT Automatic target recognition (ATR) is a crucial application for synthetic aperture radar (SAR). This paper presents an ATR method with the scattering centre (SC) based on the world view vector (WVV) and the weighted bipartite graph model (WBGM). Targets are separated by the filter-based cluster size insensitive enhanced fuzzy c-mean cluster (csiEnFCM) algorithm before feature extraction. Later, WVV-based feature set is constructed with the extracted SCs. Subsequently, the WBGM is applied to recognize target by matching its feature set with templates. Experiments on the moving and stationary target recognition (MSTAR) dataset demonstrate that the proposed method performs well in ATR.

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