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dc.contributor.authorCalise, Anthony J.
dc.contributor.authorJohnson, Eric N.
dc.contributor.authorSattigeri, Ramachandra J.
dc.contributor.authorWatanabe, Yoko
dc.contributor.authorMadyastha, Venkatesh
dc.date.accessioned2010-11-09T17:04:35Z
dc.date.available2010-11-09T17:04:35Z
dc.date.issued2005-06
dc.identifier.urihttp://hdl.handle.net/1853/35865
dc.descriptionPresented at the 2005 American Control Conference; June 8-10, 2005; Portland, OR, USA.en_US
dc.description.abstractThis paper discusses estimation and guidance strategies for vision-based target tracking. Specific applications include formation control of multiple unmanned aerial vehicles (UAVs) and air-to-air refueling. We assume that no information is communicated between the aircraft, and only passive 2-D vision information is available to maintain formation. To improve the robustness of the estimation process with respect to unknown target aircraft acceleration, the nonlinear estimator (EKF) is augmented with an adaptive neural network (NN). The guidance strategy involves augmenting the inverting solution of nonlinear line-of-sight (LOS) range kinematics with the output of an adaptive NN to compensate for target aircraft LOS velocity. Simulation results are presented that illustrate the various approaches.en_US
dc.description.sponsorshipThis work was supported in part by AFOSR MURI #F49620-03-1- 0401: Active Vision Control Systems for Complex Adversarial 3-D Environments.
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectEstimationen_US
dc.subjectGuidanceen_US
dc.subjectTarget trackingen_US
dc.subjectVisionen_US
dc.titleEstimation and Guidance Strategies for Vision-based Target Trackingen_US
dc.typeProceedingsen_US
dc.contributor.corporatenameGeorgia Institute of Technology. School of Aerospace Engineering
dc.publisher.originalAACC


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