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D2S证据理论在多传感器目标识别中的应用
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2009-06-27
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针对多传感器目标信号的特点,运用小波变换和FOBW编码对信号进行特征提取。在此基础上,运用D2S 证据理论对目标进行融合识别。与单一传感器的识别结果相比较,上述方法能明显提高识别能力,同时降低识别的不确定性,提高识别的实时性。
关键词: 传感器; D2S 证据理论; 小波变换; FOBW编码; 模式识别
Abstract : Wavelet transform and FOBW coding are used to extract the target’s features of acoustic and seismic signals. And then ,D2S evidential theory is used to identify the target based on wavelet transform and FOBWcoding.By comparing the simulation results of targets identification based on separate data and fusion data respectively ,the advantages of this
algorithm are testified because of its higher identification rate and better real2time.
Key words : sensors ; D2S evidential theory ; wavelet transform; FOBW coding ; model recognition
关键词: 传感器; D2S 证据理论; 小波变换; FOBW编码; 模式识别
Abstract : Wavelet transform and FOBW coding are used to extract the target’s features of acoustic and seismic signals. And then ,D2S evidential theory is used to identify the target based on wavelet transform and FOBWcoding.By comparing the simulation results of targets identification based on separate data and fusion data respectively ,the advantages of this
algorithm are testified because of its higher identification rate and better real2time.
Key words : sensors ; D2S evidential theory ; wavelet transform; FOBW coding ; model recognition
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