Perimeter intrusion detection and intruder classification

James F. Smith III

doi:10.1117/12.819895

11 May 2009 Perimeter intrusion detection and intruder classification

James F. Smith III

Proceedings Volume 7336, Signal Processing, Sensor Fusion, and Target Recognition XVIII; 73361I (2009) https://doi.org/10.1117/12.819895
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

Abstract

A fuzzy logic perimeter intrusion classification algorithm (FLPICA) has been developed to determine when intruders have crossed a perimeter and to classify the type of intrusion. The FLPICA works in real-time and makes its decisions based on data from single or multiple geophones. Extensive discussions of some of the fuzzy decision trees and fuzzy membership functions making up the algorithm are provided. The geophones can be one to three axes geophones, i.e., they can provide information in only one dimension or three. The FLPICA uses various signal processing algorithms to extract the quantities that facilitate decisions. The parameters that are extracted in real time from the data are the cadence of walkers, runners, jumpers, etc.; the bearing of intruders; power measures for the signal; and the signal's kurtosis. The FLPICA is applicable to many different environments and can be retrained as needed. It is based on rules born of human expertise. The FLPICA is applicable to many different scenarios, e.g., classifying intruders as walkers, runners, creepers, orbiters, jumpers, vehicles, animals, etc. It can also make a declaration as to the threat status of the intruder. The FLPICA can separate the signal of a human intruder on foot from those of vehicles and other noise sources. Examples where the intruder exhibits the behaviors of walkers, runners, creepers and orbiters are provided. Theoretical and simulation results are discussed.

Citation Download Citation

James F. Smith III "Perimeter intrusion detection and intruder classification", Proc. SPIE 7336, Signal Processing, Sensor Fusion, and Target Recognition XVIII, 73361I (11 May 2009); https://doi.org/10.1117/12.819895

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