Nonlinear Deterministic Filter for Inertial Navigation and Bias Estimation with Guaranteed Performance
Systems and Control
2021-09-20 v1 Systems and Control
Abstract
Unmanned vehicle navigation concerns estimating attitude, position, and linear velocity of the vehicle the six degrees of freedom (6 DoF). It has been known that the true navigation dynamics are highly nonlinear modeled on the Lie Group of . In this paper, a nonlinear filter for inertial navigation is proposed. The filter ensures systematic convergence of the error components starting from almost any initial condition. Also, the errors converge asymptotically to the origin. Experimental results validates the robustness of the proposed filter.
Cite
@article{arxiv.2109.08654,
title = {Nonlinear Deterministic Filter for Inertial Navigation and Bias Estimation with Guaranteed Performance},
author = {Ajay Singh Ludher and Marium Tawhid and Hashim A. Hashim},
journal= {arXiv preprint arXiv:2109.08654},
year = {2021}
}
Comments
24th International Intelligent Transportation Systems Conference