• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.6
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• pp.1129-1137
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• 2011

This paper reports on a design of the footstep signal detection system using the seismic sensor. First, we analyzed the characteristics of seismic signal, seismic sensor, and the UGS(Unattended Ground Sensor) system with seismic sensors. In addition, we summarized the existing algorithms to detect footstep using the seismic sensors, and developed our low-power and high efficient footstep detection algorithm. In this paper, the sensor node operations are classified into three different steps and different resources and algorithms are applied to each step, not only to minimize the power consumption, but also to improve the performance.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.258-266
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• 2013

We propose adaptive detection algorithm to reduce a false alarm by considering the characteristics of the random noise on the detection system based on a seismic sensor. The proposed algorithm consists of the first step detection using kernel function and the second step detection using detection classes. Kernel function of the first step detection is obtained from the threshold of the Neyman-Pearon decision criterion using the probability density functions varied along the noise from the measured signal. The second step detector consists of 4 step detection class by calculating the occupancy time of the footstep using the first detected samples. In order to verify performance of the proposed algorithm, the detection of the footsteps using measured signal of targets (walking and running) are performed experimentally. The detection results are compared with a fixed threshold detector. The first step detection result has the high detection performance of 95% up to 10m area. Also, the false alarm probability is decreased from 40% to 20% when it is compared with the fixed threshold detector. By applying the detection class(second step detector), it is greatly reduced to less than 4%.