Title :
Multisensor integration in the tracking of landing aircraft
Author :
Korona, Zbigniew ; Kokar, Mieczyslaw M.
Author_Institution :
Dept. of Ind. Eng. & Inf. Syst., Northeastern Univ., Boston, MA, USA
Abstract :
An algorithm is presented for tracking a landing aircraft using two different passive sensors, a laser range finder (LRF) and an infrared camera (FLIR). The main feature of this algorithm is its ability to identify and compensate for plume disturbance. The algorithm is based on the extended Kalman filter (EKF) and the filtering confidence function (FCF) which introduces a learning approach to the tracking problem. The results of a simulation using the learning tracking algorithm and the extended Kalman filter alone are presented and compared
Keywords :
Kalman filters; aircraft; filtering theory; laser ranging; learning systems; optical tracking; sensor fusion; IR camera; extended Kalman filter; filtering confidence function; infrared camera; landing aircraft tracking; laser range finder; learning tracking algorithm; multisensor integration; passive sensors; plume disturbance; Aircraft propulsion; Cameras; Filtering; Filters; Industrial engineering; Information systems; Infrared sensors; Radar tracking; Sensor fusion; Target tracking;
Conference_Titel :
Multisensor Fusion and Integration for Intelligent Systems, 1994. IEEE International Conference on MFI '94.
Conference_Location :
Las Vegas, NV
Print_ISBN :
0-7803-2072-7
DOI :
10.1109/MFI.1994.398377
