DocumentCode :
2982978
Title :
Kalman filter residual expert system
Author :
Grimshaw, Captain Jeff ; Amburn, Major Phil
Author_Institution :
AFIT/ENG, Wright-Patterson AFB, OH, USA
fYear :
1988
fDate :
23-27 May 1988
Firstpage :
360
Abstract :
The Pilot´s Associate (PA) program has been initiated to help mitigate the extensive workload of the fighter pilot. The PA must continually monitor and evaluate important aircraft, weapon, and threat systems as well as terrain and weather conditions by means of sensor systems. The data from these systems must be fused together to present the PA with a coherent picture of the environment. One common technique for fusing sensor data uses Kalman filters in a multiple model adaptive filter (MMAF). An improved filter selection technique is presented as part of an advanced MMAF. A knowledge-based system is used to augment the usual selection technique. Preliminary results indicate that this approach helps in situations that are known to cause problems for Kalman filter-based MMAF systems
Keywords :
Kalman filters; aerospace computing; computerised signal processing; expert systems; military computing; Kalman filters; Pilot´s associate program; aircraft; computerised signal processing; fighter pilot; knowledge-based system; multiple model adaptive filter; residual expert system; sensor systems; threat systems; weapon; weather; Aircraft navigation; Artificial intelligence; Condition monitoring; Expert systems; Filters; Intelligent sensors; Phased arrays; Sensor arrays; Sensor fusion; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Aerospace and Electronics Conference, 1988. NAECON 1988., Proceedings of the IEEE 1988 National
Conference_Location :
Dayton, OH
Type :
conf
DOI :
10.1109/NAECON.1988.195037
Filename :
195037
Link To Document :
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