Wavelet denoising and feature extraction of seismic signal for footstep detection

Seismic sensors are widely used to detect moving target in ground sensor networks. Footstep detection is very important for security surveillance and other applications. Because of non-stationary characteristic of seismic signal and complex environment conditions, footstep detection is a very challenging problem. A novel wavelet denoising method based on singular value decomposition is used to solve these problems. The signal-to-noise ratio (SNR) of raw footstep signal is greatly improved using this strategy. The feature extraction method is also discussed after denosing procedure. Comparing, with kurtosis statistic feature, the wavelet energy feature is more promising for seismic footstep detection, especially in a long distance surveillance.

Seismic sensors are widely used to detect moving target in ground sensor networks. Footstep detection is very important for security surveillance and other applications. Because of non-stationary characteristic of seismic signal and complex environment conditions, footstep detection is a very challenging problem. A novel wavelet denoising method based on singular value decomposition is used to solve these problems. The signal-to-noise ratio (SNR) of raw footstep signal is greatly improved using this strategy. The feature extraction method is also discussed after denosing procedure. Comparing, with kurtosis statistic feature, the wavelet energy feature is more promising for seismic footstep detection, especially in a long distance surveillance.

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Machine Learning & Cybernet Res Inst.; IEEE SMC Soc.; Chinese Assoc Artificial Intelligence.; Univ Sci & Technol Beijing.; Tsinghua Univ.; Peking Univ.; Chongqing Univ.; Hebei Univ.; Hong Kong Baptist Univ.; Natl Nat Sci Fdn China.

[Xing, Huai-Fei; Li, Fang; Liu, Yu-Liang] Chinese Acad Sci, Inst Semicond, State Key Lab Integrated Optoelect, Beijing 100083, Peoples R China

Machine Learning & Cybernet Res Inst.; IEEE SMC Soc.; Chinese Assoc Artificial Intelligence.; Univ Sci & Technol Beijing.; Tsinghua Univ.; Peking Univ.; Chongqing Univ.; Hebei Univ.; Hong Kong Baptist Univ.; Natl Nat Sci Fdn China.