Analysis of track fusion using the reduced state estimator

We evaluate the performance of track fusion of two-state tracks based on individual track estimates. The individual track estimates are evaluated using a Reduced State Estimator that provides a separate estimate of the filtered random error and the bias resulting from target acceleration. By separating the bias and random portions of the errors, the filters and fusion process can be optimized to minimize cost functions specific to each application.