Information fusion in airborne integrated navigation

An advanced algorithm is adopted to improve the accuracy and reliability of the aircraft navigation system, which is based on strap-down inertial navigation system (SINS), Global Positioning System (GPS) and tactical air navigation system (TACAN). The data fusion is achieved by using federated Kalman filtering method, choosing the error of navigation parameter as the state vector, and modeling state equation. The estimation of state vector is accomplished in subfilters by using the indirect filtering method. The mutual state vector of each subfilter is detected and fused in primary filter, which can output the optimal and reliable estimation of navigation parameter error. The simulation results show that the algorithm can improve the accuracy of the navigation system. The integrated navigation system is feasible with good fault tolerance and reliability.