DocumentCode :
1628438
Title :
Kalman filter and ARMA filter as approach to multiple sensor data fusion problem
Author :
Munoz Gutierrez, M.A. ; Florez Zuluaga, J.A. ; Kofuji, S.T.
Author_Institution :
Lab. de Sist. Integraveis, Escola Politec. da USP, Sao Paulo, Brazil
fYear :
2013
Firstpage :
1
Lastpage :
6
Abstract :
The Air Traffic Control (ATC) systems are critical due the amount of information that they have to process in real time. These systems combined different kind of information, like primary and secondary radar information and flight planning information. Depending the extent of a country different RADAR are installed trying to cover most of the country area. This could become a problem, because different RADAR can detect and locate the same object at different position on the map, this is a multiple sensor data fusion problem. In this paper we present a technique that combines conventional Kalman filter techniques with an ARMA filter to provide a solution to the problem. Multiple objects tracking examples are presented.
Keywords :
Kalman filters; air traffic control; autoregressive moving average processes; radar tracking; sensor fusion; ARMA filter; ATC; Kalman filter; air traffic control; country different RADAR; flight planning information; multiple objects tracking examples; multiple sensor data fusion problem; primary radar information; secondary radar information; Airborne radar; Aircraft; Kalman filters; Radar detection; Radar tracking; Trajectory; Kalman and ARMA filter; Radar tracking; multi-sensor Fusion; trajectory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Security Technology (ICCST), 2013 47th International Carnahan Conference on
Conference_Location :
Medellin
Type :
conf
DOI :
10.1109/CCST.2013.6922059
Filename :
6922059
Link To Document :
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