An Online Evaluation Based Extended-State Kalman Filter Approach to Navigation Via Signal of Opportunity

This paper studies the problem of multi-source opportunistic signal navigation of aircraft. Firstly, the paper provides the mathematical models for five types of opportunistic signals. Furthermore, the online evaluation algorithm based on T-test is proposed for seeking the biased opportunistic signals. By disposing of the opportunistic signals causing intolerant location error, an estimated location position is obtained by trusty opportunistic signals. Finally, to handle the unknown part of flight acceleration caused by external disturbances, the extended-state Kalman filter is constructed to promote the locating accuracy. The simulation results show the effectiveness of the proposed method.