Estimation covariance of measurement fusion on track-to-track problem

Measurement fusion is an optimal data fusion algorithm. The covariance of measurement fusion is proved to be decided by a function of the measurement matrix and measurement noise covariance. The greater the function is, the less the covariance measurement fusion method can obtain. Therefore, the estimation accuracy increases when the function increase. The results of simulation agree with the theoretical results.