Nonlinear Estimation for Position-Aided Inertial Navigation Systems

TL;DR

This paper presents a nonlinear observer for 3D inertial navigation that accurately estimates vehicle states from IMU and position data, ensuring stability without assumptions on acceleration.

Contribution

It introduces a novel nonlinear estimation scheme that guarantees semi-global exponential stability without auxiliary states or acceleration assumptions.

Findings

Outperforms existing methods in simulations

Guarantees stability without acceleration assumptions

Estimates full vehicle state accurately

Abstract

In this work we solve the position-aided 3D navigation problem using a nonlinear estimation scheme. More precisely, we propose a nonlinear observer to estimate the full state of the vehicle (position, velocity, orientation and gyro bias) from IMU and position measurements. The proposed observer does not introduce additional auxiliary states and is shown to guarantee semi-global exponential stability without any assumption on the acceleration of the vehicle. The performance of the observer is shown, through simulation, to overcome the state-of-the-art approach that assumes negligible accelerations.