Integrated Navigation Filtering Algorithm in Complex Environments

Abstract-Though the GNSS/SINS has been widely used to provide high-precision and high-integrity services for many aeronautical applications, GNSS is vulnerable to interference because of its low signal strength, leading to the accuracy degradation of the integrated navigation. To solve this problem, an adaptive Kalman algorithm introduces adaptive factor to adjust filter parameters in real time, so as to ensure the accuracy of integrated navigation in complex environments. Firstly, the state equation and observation equation of the integrated navigation system are determined based on the error equation of SINS. Secondly, the state transition matrix and white noise of the system are equivalently discretized, and then the data is filtered by the adaptive Kalman filter algorithm. Finally, the simulation results show that the adaptive Kalman filter algorithm can improve the integrated navigation accuracy, especially in complex environments.