The impulse radio(IR)ultra-wideband(UWB)through wall radar plays an important role in the field of through wall human behavior recognition due to its good penetration and range resolution.However,the conventional recognition method,only uses single domain feature to describe the behavior pattern,and the recognition accuracy is not high.Aiming at this problem,an IR-UWB through wall radar human behavior recognition algorithm is proposed based on time-frequency domain feature fusion.Firstly,the human behavior range image with high signal-to-noise ratio is obtained by clutter suppression and distance compensation methods.Secondly,the time domain features of the target are extracted based on the range image.It is fused with frequency domain features to build data set.Finally,human behavior is identified based on support vector machine(SVM)algorithm.Experimental results show that the proposed algorithm can achieve 95％accuracy for human behavior recognition with IR-UWB through wall radar.
关键词
人体行为识别/冲激脉冲超宽带雷达/特征提取/支持向量机
Key words
human behavior recognition/impulse radio(IR)ultra-wideband(UWB)radar/feature extraction/support vector machine(SVM)
维普
万方数据