Title :
Federated filter for fault-tolerant integrated navigation systems
Author :
Carlson, Neal A.
Author_Institution :
Integrity Syst. Inc., Winchester, MA, USA
fDate :
29 Nov-2 Dec 1988
Abstract :
An efficient, federated Kalman filtering method is presented, based on rigorous information-sharing principles. The method applies to decentralized navigation systems in which one or more sensor-dedicated local filters feed a larger master filter. The local filters operate in parallel, processing unique data from their local sensors, and common data from a shared inertial navigation system. The master filter combines local filter outputs at a selectable reduced rate, and yields estimates that are globally optimal or subset-optimal. The method provides major improvements in throughput (speed) and fault tolerance, and is well suited to real-time implementation. Practical federated filter examples are presented, and discussed in terms of structure, accuracy, fault tolerance, throughput, data compression, and other real-time issues
Keywords :
Kalman filters; filtering and prediction theory; inertial navigation; Kalman filtering; accuracy; data compression; decentralized navigation systems; fault-tolerant integrated navigation systems; information-sharing; master filter; real-time implementation; real-time issues; sensor-dedicated local filters; shared inertial navigation system; structure; throughput; Data compression; Fault tolerance; Fault tolerant systems; Feeds; Filtering; Inertial navigation; Kalman filters; Sensor systems; Throughput; Yield estimation;
Conference_Titel :
Position Location and Navigation Symposium, 1988. Record. Navigation into the 21st Century. IEEE PLANS '88., IEEE
Conference_Location :
Orlando, FL
DOI :
10.1109/PLANS.1988.195473