Optimal Distributed Kalman and Lainiotis Filters: Optimal Uniform Distribution of Measurements into Local Processors

A method to implement the optimal distributed Kalman and Lainiotis filters is proposed. The method is based on the a-priori determination of the optimal uniform distribution of the measurements into parallel processors, in the sense of minimizing the computation time. The resulting optimal Kalman and Lainiotis filters present high parallelism speedup. This result 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.