Seismic detection algorithm and sensor deployment recommendations for perimeter security

Abstract

Field studies were conducted in 2005 in Yuma, Arizona at the Yuma Proving Grounds (YPG) to document seismic signatures of walking humans. Walker-generated vertical ground vibrations were recorded using standard omni-directional 4.5 Hz peak-resonance geophones. Walker position and speed were measured using portable GPS equipment. Collected seismic data were processed and hypothetical sensor performance predictions were made using an algorithm developed for the detection and classification of a walking intruder. Sample results for the Yuma study are presented in the form of sensor detection/classification vs. range plots, and color-coded animations of seismic sensor alarm annunciations during walking intruder tests. A perimeter intrusion scenario for a Forward Operating Base is defined that involves a walker approaching a sensor picket-line along a path exactly halfway between two adjacent sensors. This is considered a conservative representation of the perimeter intrusion problem. Summary plots derived from a binomial probability based analysis define intruder detection probabilities for different sensor spacings. For a 215 lb intruder walking in the Yuma test environment, a 90% probability of at least two walker-classified sensor detections is achieved at a sensor spacing of 140 m. Preliminary investigations show the intruder classification component of the discussed detection/classification algorithm to perform well at rejecting signals associated with a nearby idling vehicle and normal background noise.