GPS-denied Navigation: Attitude, Position, Linear Velocity, and Gravity Estimation with Nonlinear Stochastic Observer

TL;DR

This paper introduces novel geometric nonlinear stochastic observers on SE2(3) for GPS-denied navigation, accurately estimating attitude, position, and velocity using IMU and landmark data, with proven stability and real-world validation.

Contribution

It develops new nonlinear stochastic observers on SE2(3) that effectively handle IMU noise and nonlinear dynamics for navigation without GPS, validated on real quadrotor data.

Findings

Observers are almost semi-globally uniformly ultimately bounded in mean square.

Effective in real-world quadrotor navigation scenarios.

Handles IMU measurement noise efficiently.

Abstract

Successful navigation of a rigid-body traveling with six degrees of freedom (6 DoF) requires accurate estimation of attitude , position, and linear velocity. The true navigation dynamics are highly nonlinear and are modeled on the matrix Lie group of SE2(3). This paper presents novel geometric nonlinear continuous stochastic navigation observers on SE2(3) capturing the true nonlinearity of the problem. The proposed observers combines IMU and landmark measurements. It efficiently handles the IMU measurement noise. The proposed observers are guaranteed to be almost semi-globally uniformly ultimately bounded in the mean square. Quaternion representation is provided. A real-world quadrotor measurement dataset is used to validate the effectiveness of the proposed observers in its discrete form. Keywords: Inertial navigation, stochastic system, Brownian motion process, stochastic filter algorithm, stochastic differential equation, Lie group, SE(3), SO(3), pose estimator, position, attitude, feature measurement, inertial measurement unit, IMU.