On the Globalized Likelihood Function for Exact Track-To-Track Fusion at Arbitrary Instants of Time

Abstract—Tracking applications in distributed sensor scenarios often suffer from small bandwidths and time delayed transmis-sions. 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