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Footstep Detection in Noisy Environment via Non-Linear Spectral Subtraction and Cross-Correlation
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 Title & Authors
Footstep Detection in Noisy Environment via Non-Linear Spectral Subtraction and Cross-Correlation
Kim, Tae-Bok; Ko, Hanseok;
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Footstep detection using seismic sensors for security is a very meaningful task, but readings can easily fluctuate due to noise in outdoor environment. We propose NSSC method based on nonlinear spectral subtraction and cross-correlation using prime footstep model signal as a footstep signal refining process that enhances the signal-to-noise ratio (SNR) and attenuates noise. After de-noising, a detection event classification method is presented as further refining process to ensure that the detection result is a footstep. To validate the proposed algorithm, representative experiments including sunny and rainy-day cases are demonstrated.
Seismic;Footstep;Nonlinear Sepctral Subtraction;Correlation;Detection;Classification;
 Cited by
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