Objectives GNSS/SINS (global navigation satellite system/strapdown inertial navigation system) integrated navigation system has been widely used and researched. In complex environment, GNSS output is prone to four phenomena, including root mean square (RMS) of error sudden change, RMS of error slow change, hard fault and soft fault, which affect the filtering accuracy of integrated navigation system and the navigation safety of carrier.
Methods In order to solve the above problems, an improved adaptive filtering algorithm for GNSS/SINS integrated navigation system is proposed. Firstly, an observation factor was constructed by using the observation anomaly test statistics and filter threshold value in the filtering process. Then, the variable Bayesian principle and the outlier-restrained filtering method are combined to design an improved adaptive filtering algorithm for the integrated navigation system.
Results The simulation experiment shows that compared with the conventional algorithms, the proposed algorithm can improve the position accuracy and speed accuracy by about 11.8% and 13.7%, respectively, when the RMS of GNSS output error changes. And it can also improve the position accuracy and speed accuracy by about 70.8% and 69.6%, respectively, when a hard fault occurs on the GNSS output.
Conclusions The experimental results show that the proposed algorithm has strong adaptability and can improve the accuracy and continuous availability of integrated navigation systems in complex environments.
DownLoad: