The objective of this proposal is the development of an improved track to track fusion algorithm for C3I employing multiple dissimilar sensors (Radar, ESM, IR, etc.). These sensors detect targets and create tracks at different data rates. Hence, there is a need to time synchronize these tracks which are updated at different times. Existing track fusion algorithms do not address this synchronization problem and exclude information contained in the cross-covariance of candidate tracks for fusion. The proposed investigation will present a soultion of the track syncronization problem. In addition, the proposed track association algorithm will show that the probability distribution of correct association and false association can be improved by incorporating the cross-covariance in the test statistic for association. A recursive equation describing the cross-covariance for synchronized tracks will be obtained. Furthermore, an expression for the steady state cross-covariance matrix will also be derived in closed form. Extend of improvement in kinematec track association and fusion by including the cross-covariance will be obtained by numerical simulation
