On the globalized likelihood function for exact track-to-track fusion at arbitrary instants of time

Tracking applications in distributed sensor scenarios often suffer from small bandwidths and time delayed transmissions. In order to save communication capacity, it is common to transmit locally preprocessed estimates on the target to a central fusion center. A global track is obtained by Track-to-Track fusion. If sensor links are only established temporarily, transmissions can only be performed irregularly. This leads to the challenge of decentralized decorrelation of local sensor tracks for a T2TF at arbitrary instants of time. In this paper, we present a modified likelihood function which employs the global covariance of the whole system. As a result, the tracks remain decorrelated and may be fused as independent information entities. Therefore, the central track fusion is independent of past estimates and obtains a globally optimal estimate.