@inproceedings{b6e264a3d18c4f57ae181aae78937f53,
title = "An INS/Lidar Integrated Navigation Algorithm Based on Robust Kalman Filter",
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.",
keywords = "GPS-denied, Integrated navigation, Lidar, Robust Kalman filter, UAV",
author = "Xuhang Liu and Xiaoxiong Liu and Yue Yang and Weiguo Zhang",
note = "Publisher Copyright: {\textcopyright} 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; International Conference on Guidance, Navigation and Control, ICGNC 2020 ; Conference date: 23-10-2020 Through 25-10-2020",
year = "2022",
doi = "10.1007/978-981-15-8155-7_86",
language = "英语",
isbn = "9789811581540",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "1027--1037",
editor = "Liang Yan and Haibin Duan and Xiang Yu",
booktitle = "Advances in Guidance, Navigation and Control - Proceedings of 2020 International Conference on Guidance, Navigation and Control, ICGNC 2020",
}