RF Emitter Tracking and Intent Assessment
AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH GRADUATE SCHOOL OF ENGINEERING AND MANAGEMENT
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Current research in employing pattern recognition techniques in a wireless sensor network WSN to detect anomalous or suspicious behavior is limited. The purpose of this research was to determine the feasibility of an accurate tracking and intent assessment system of unknown or foreign radio frequency RF emitters in close proximity to and within military installations as a method for physical security. 22 position tracks were collected using a hand-held Global Positioning System GPS unit and a training data set from five di erent features was generated for each position track. Each collected position track was individually classified as suspicious or non-suspicious by the leave-one-out-cross-validation LOOCV method using four di erent classification methods. The four classification methods used in this research were the linear discriminant function LDF, the diagonal linear discriminant function DLDF, the quadratic discriminant function QDF and the Mahalanobis distance method. The accuracies and false positivenegative error rates of the four classification methods were compared for di erent assessment system configurations. Additionally, best fit receiver operating characteristic ROC curves were generated for each classification method and discussed. The QDF classification method out-performed the other three classification methods. This classification method achieved an accuracy of 95 when it classified the 22 position tracks one at a time. The lowest false positive and false negative rates were 10 and 0, respectively. The prior probabilities for the non-suspicious and suspicious classes were both set to 50 class for this configuration.
- Electricity and Magnetism