Abstract
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.
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Sharma, R., Yoder, J., Kwon, H., Pack, D. (2014). Vision Based Mobile Target Geo-localization and Target Discrimination Using Bayes Detection Theory. In: Ani Hsieh, M., Chirikjian, G. (eds) Distributed Autonomous Robotic Systems. Springer Tracts in Advanced Robotics, vol 104. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55146-8_5
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DOI: https://doi.org/10.1007/978-3-642-55146-8_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-55145-1
Online ISBN: 978-3-642-55146-8
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