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We propose a new CFAR detector based on the environment learning for improving the radar target detection performance in complex environments. A new algorithm is presented for radar environment recognition by combining the histogram and bagged CART technique. The histogram is used to extract the effective features which in turn serve as the inputs for the bagged CART algorithm. The proposed CFAR detector is an adaptive algorithm composed of CA CFAR and OS CFAR based on the classification of radar environments. The tests with real data show that the classification of radar environments achieves a higher score than that one given recently and the proposed CFAR detector has a better performance than CA CFAR, OS CFAR and EA CFAR detectors.
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