Abstract: This paper presents a new algorithm making use of kurtosis, which is a statistical parameter, to distinguish the seismic signal generated by a person's footsteps from other signals. It is adaptive to any environment and needs no machine study or training. As persons or other targets moving on the ground generate continuous signals in the form of seismic waves, we can separate different targets based on the seismic waves they generate. The parameter of kurtosis is sensitive to impulsive signals, so it’s much more sensitive to the signal generated by person footsteps than other signals generated by vehicles, winds, noise, etc. The parameter of kurtosis is usually employed in the financial analysis, but rarely used in other fields. In this paper, we make use of kurtosis to distinguish person from other targets based on its different sensitivity to different signals. Simulation and application results show that this algorithm is very effective in distinguishing person from other targets.
Keywords: Kurtosis; peakedness; tail; seismic signal; person identification
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Liang, Z.; Wei, J.; Zhao, J.; Liu, H.; Li, B.; Shen, J.; Zheng, C. The Statistical Meaning of Kurtosis and Its New Application to Identification of Persons Based on Seismic Signals. Sensors 2008, 8, 5106-5119.
Liang Z, Wei J, Zhao J, Liu H, Li B, Shen J, Zheng C. The Statistical Meaning of Kurtosis and Its New Application to Identification of Persons Based on Seismic Signals. Sensors. 2008; 8(8):5106-5119.
Liang, Zhiqiang; Wei, Jianming; Zhao, Junyu; Liu, Haitao; Li, Baoqing; Shen, Jie; Zheng, Chunlei. 2008. "The Statistical Meaning of Kurtosis and Its New Application to Identification of Persons Based on Seismic Signals." Sensors 8, no. 8: 5106-5119.