A Sliding Window Filter With GNSS-State Constraint for RTK-Visual-Inertial Navigation

• Published in: IEEE transactions on robotics Vol. 40; pp. 1920 - 1937
• Main Authors: Huang, Xiaohong, Yang, Cui, Wen, Miaowen
• Format: Journal Article
• Language: English
• Published: New York IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Ambiguity resolution (mathematics); Antenna measurements; Global navigation satellite system; Inertial navigation; Kinematics; Position measurement; Real time; Real-time kinematic (RTK); Robot sensing systems; satellite navigation systems; Satellites; sensor fusion; simultaneous localization and mapping (SLAM); Sliding; Velocity measurement; visual-inertial odometry; Visualization
• ISSN: 1552-3098; 1941-0468
• DOI: 10.1109/TRO.2024.3365008

In this article, we present a novel method by using a sliding window filter (SWF) for real-time kinematic (RTK) visual-inertial navigation. Unlike other recent works that retain only the states of visual keyframes to reduce computational complexity, we additionally retain the GNSS states (i.e., position, orientation, and velocity of the body and inertial biases at the time of capturing GNSS measurements) in the SWF to construct more appropriate constraints between measurements and states. In order to make the method run as a real-time system, especially when the SWF contains numerous GNSS states, we propose a parallel elimination strategy in a predefined elimination ordering, which can solve the Gauss-Newton problem and simultaneously obtain the covariance for ambiguity resolution (AR). We reveal when and how the system improves the AR performance. Moreover, we analyze the observability of the system under different conditions. We also conduct experiments in the real world and compare the results with the state-of-the-art. Experimental results show that the proposed method is able to achieve a higher and stabler fixed rate in GNSS challenging environments, and has better positioning performance with or without measurements of a base station. We have decided to publish the code of our work for the community.