Abstract
Aiming at positioning requirement of UAV in GPS-denied Environment, an Inertial Navigation System (INS)/lidar algorithm based on Robust Kalman Filter (RKF) is proposed. The scan matching is selected to process the lidar information and obtain the position. After that, the INS/lidar model was constructed by using INS error model, in order to suppress the interference of measurement outliers on the navigation solution, RKF algorithm is introduced to reduce the influence of measurement outliers on filtering result. Experiment results indicate that the proposed algorithm can obtain precise position and attitude in GPS-denied environment, and suppress the influence of measurement outliers on filtering result.
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Acknowledgements
This research was supported by the National Natural Science Foundation of China (No. 61573286 and No. 61374032), and the research was funded by Shaanxi Province Key Laboratory of Flight Control and Simulation Technology.
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Liu, X., Liu, X., Yang, Y., Zhang, W. (2022). An INS/Lidar Integrated Navigation Algorithm Based on Robust Kalman Filter. In: Yan, L., Duan, H., Yu, X. (eds) Advances in Guidance, Navigation and Control . Lecture Notes in Electrical Engineering, vol 644. Springer, Singapore. https://doi.org/10.1007/978-981-15-8155-7_86
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DOI: https://doi.org/10.1007/978-981-15-8155-7_86
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