A practical tracking algorithm of multisensor data fusion

This paper describes an algorithm for fusion of tracks created by radar and IR sensor with different dimensional measurement data. It is assumed these sensors are asynchronous and the measurement data are transmitted to a central station at different rates. By means of the technique of time matching two asynchronous data are fused and then the filter is updated according to the fused information. The rotation Kalman filter algorithm to data fusion is discussed. This approach can effectively solve the problem of nonlinear measurement and reduce the load of calculation.