On optimal distributed kalman filtering and retrodiction at arbitrary communication rates for maneuvering targets

Track-to-track fusion aims at combining locally preprocessed information of individual sensors optimally, i.e. in a way that is equivalent to fusing all measurements of all sensors directly. It is well known that this can be achieved if the local sensor tracks produced at all individual scan times are available in the fusion center. Full-rate communication in this sense, however, is impractical in many applications. We thus propose a distributed Kalman-type processing scheme, which provides optimal track-to-track fusion results at arbitrarily chosen instants of time by communicating and combining the local sensor dasiatrackspsila referring to this time.