Optimal decentralized Kalman filter and Lainiotis filter
A method to implement the optimal decentralized Kalman filter and the optimal decentralized Lainiotis filter is proposed; the method is based on the a priori determination of the optimal distribution of measurements into parallel processors, minimizing the computation time. The resulting optimal Kalman filter and optimal Lainiotis filter require uniform distribution or near to uniform distribution of measurements into parallel processors. The optimal uniform distribution has the advantages of elimination of idle time for the local processors and of low hardware cost, but it is not always applicable. The optimal filters present high parallelism speedup; this is verified through simulation results and is very important due to the fact that, in most real-time applications, it is essential to obtain the estimate in the shortest possible time.
optimization kalman filter lainiotis filter discrete time decentralized algorithms analysis of algorithms