Footstep Detection in Noisy Environment via Non-Linear Spectral Subtraction and Cross-Correlation 


Vol. 39,  No. 1, pp. 60-69, Jan.  2014


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  Abstract

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.

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  Cite this article

[IEEE Style]

T. Kim and H. Ko, "Footstep Detection in Noisy Environment via Non-Linear Spectral Subtraction and Cross-Correlation," The Journal of Korean Institute of Communications and Information Sciences, vol. 39, no. 1, pp. 60-69, 2014. DOI: .

[ACM Style]

Tae-bok Kim and Hanseok Ko. 2014. Footstep Detection in Noisy Environment via Non-Linear Spectral Subtraction and Cross-Correlation. The Journal of Korean Institute of Communications and Information Sciences, 39, 1, (2014), 60-69. DOI: .

[KICS Style]

Tae-bok Kim and Hanseok Ko, "Footstep Detection in Noisy Environment via Non-Linear Spectral Subtraction and Cross-Correlation," The Journal of Korean Institute of Communications and Information Sciences, vol. 39, no. 1, pp. 60-69, 1. 2014.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880