Vehicle acoustic signals in battlefield

which consist of many different components are very complex. Because a single acoustic feature Can hardly reflect full characteristics of the vehicle

multiple features should be extracted to form characteristic vector.Vehicle acoustic signals are separated from all the acquired signals by using modified CFAR algorithm.The three features are extracted

including harmonic set

MFCC and wavelet energy.But the resulting feature vector is too large

so PCA method is applied to reduce the dimension of feature vector.The experiment results show that the combined three features are better than the single feature in classification performance and the identification rate can reach above 90%.