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

机译:基于散射中心特征和二部图匹配的SAR ATR方法

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摘要

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.
机译:自动目标识别(ATR)是合成孔径雷达(SAR)的关键应用。本文提出了一种基于世界视图矢量(WVV)和加权二部图模型(WBGM)的散射中心(SC)的ATR方法。在特征提取之前,通过基于过滤器的群集大小不敏感的增强型模糊c均值群集(csiEnFCM)算法将目标分离。之后,使用提取的SC构建基于WVV的功能集。随后,通过将WBGM的特征集与模板进行匹配,WBGM被应用于识别目标。在动目标识别数据集上的实验表明,该方法在ATR中表现良好。

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