A low-level control policy for data fusion

A procedure to regulate the feedback signals of multiple sensors, at different rates, inside of a low-level control loop using data fusion has been developed and tested in simulation. The procedure is independent of the fusion method, and applicable to sensors with widely different sampling rates. Thus, it permits the use of "secondary" sensors, which may be available to the system for other purposes, to monitor sensor fault or failure occurrence, provide smooth transition for the system on fault, and provide a way to dynamically reconfigure the sensing system based on sensor signals uncertainty. In this procedure, sensor signals are time-correlated using Kalman filters, before being fused together. To regulate the fused feedback signal when there is no data available from the slower sensors, a Kalman filter is used to observe and generate a prediction of the fused measurement signal in place of the slower sensors measurement. Since the slow sensor lag compensation and fused measurement stabilization are independent of the fusion process, any real-time data fusion process can be used with this procedure.