Asynchronous Multi-Radar Tracking Fusion with Converted Measurements

In tracking applications, multiple radars used to observe target motion usually work asynchronously due to different sampling rates and initial sampling time instants, and the fusion time instant at the fusion center can be designated arbitrarily. In this paper, the estimation fusion problem for target tracking with asynchronous multi-rate multi-radar measurements is investigated. Two asynchronous fusion algorithms are proposed, i.e., batch time-aligned asynchronous fusion with unbiased converted measurements and sequential linear minimum mean square error (LMMSE) asynchronous fusion with converted measurements. The batch time-aligned asynchronous fusion algorithm is suboptimal because of the correlation between measurement error covariance and measurement itself. The sequential LMMSE asynchronous fusion algorithm is theoretically optimal in the sense of minimizing the mean square error within the set of all linear estimators. Numerical examples are provided to demonstrate the effectiveness of the proposed two asynchronous fusion algorithms.