Correlated tracks asynchronous fusion based on linear least squares estimation

Most of the existing algorithms for multi-sensor tracks fusion are based on sensors with the same sampling rate, ignoring communication delay and different initial time. In this paper, a method to fuse information of asynchronous sensor tracks is proposed. At the track fusion center, position and velocity information of two sensors with different sampling rates and communication delays are fused. The fused track is an asynchronous track, which has minimum error covariance. This proposed fusion method not only avoids the time correction of asynchronous data, but also improves the tracking performance of multiple sensors. The performance of the proposed algorithm is also studied.