Comparison of federated and centralized Kalman filters with fault detection considerations

This paper examines the results obtained by simulating an aircraft navigation system with a partial complement of a typical avionics sensor array using two different techniques of estimation processes: the conventional Kalman and the federated filter architectures. Areas of interest include error state estimation accuracy, residual behavior under induced sensor failure conditions, and potential for failure detection and isolation. Several simulations were accomplished for each filter design and the results were compared in order to verify the validity of the recently developed federated filter architecture. Comparison of the error state estimation accuracies of the two filter designs revealed excellent overall performances for both. The identification of failures showed a definite advantage in the federated filter design. Having sensor-dedicated local filters allowed for easy sensor failure identification for the federated filter, while the centralized filter design suffered from navigation solution corruption. Once established as a valuable estimation technique, the federated filter will add significantly to the viable alternatives when choosing a filter architecture for avionics modifications or implementations