Vision Based Mobile Target Geo-localization and Target Discrimination Using Bayes Detection Theory

In this paper, we develop a technique to discriminate ground moving targets when viewed from cameras mounted on different fixed wing unmanned aerial vehicles (UAVs). First, we develop a extended kalman filter (EKF) technique to estimate position and velocity of ground moving targets using images taken from cameras mounted on UAVs. Next, we use Bayesian detection theory to derive a log likelihood ratio test to determine if the estimates of moving targets computed at two different UAVs belong to a same target or to two different targets. We show the efficacy of the log likelihood ratio test using several simulation results.