An Airborne LiDAR/INS Integrated Navigation Algorithm based on Fuzzy Controlled SIFT

Haowei Xu, Baowang Lian, Charles K. Toth, Dorota Grejner-Brzezinska

Peer Reviewed

Abstract:	GNSS/INS integrated navigation has been widely used in airborne LiDAR mapping and other applications. The long term accuracy of INS is enhanced by frequent and stable updates of the highly precise navigation estimations provided by GNSS. However, GNSS-challenged environments exist where continuous signal or the required number of satellites are unavailable, significantly fading, or intentionally jammed, which can badly degrade the performance of the navigation solution, resulting in the cumulative INS drift error. In this situation, the role of the sensors can be reversed, LiDAR with it superior performance can replace the GNSS sensor by providing fixes for the drifting IMU. Initial studies have shown its potential for terrain referenced navigation due to its high accuracy, resolution, update rate and anti-jamming abilities. This paper describes a novel algorithm that uses scanning LiDAR ranging data and a reference database to calculate the navigation solution of the platform and then further fuse with the INS output data. Simulation results show that, when comparing with the existing algorithms, the proposed algorithm improves the LiDAR positioning accuracy. The proposed fusion algorithm improves the trajectory estimation accuracy, especially when flying over a moderately undulated terrain or flying with large roll or pitch angels.
Published in:	Proceedings of the 2017 International Technical Meeting of The Institute of Navigation January 30 - 2, 2017 Hyatt Regency Monterey Monterey, California
Pages:	313 - 326
Cite this article:	Xu, Haowei, Lian, Baowang, Toth, Charles K., Grejner-Brzezinska, Dorota, "An Airborne LiDAR/INS Integrated Navigation Algorithm based on Fuzzy Controlled SIFT," Proceedings of the 2017 International Technical Meeting of The Institute of Navigation, Monterey, California, January 2017, pp. 313-326. https://doi.org/10.33012/2017.14890
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