Nonlinear State Estimation for Inertial Navigation Systems With Intermittent Measurements
This work addresses state estimation for inertial navigation systems, which is incremental as it builds on existing observer designs with new hybrid approaches.
The paper tackles the problem of estimating attitude, position, and linear velocity for vehicles in 3D navigation using intermittent landmark measurements, proposing hybrid nonlinear observers that achieve exponential stability with a large domain of attraction.
This paper considers the problem of simultaneous estimation of the attitude, position and linear velocity for vehicles navigating in a three-dimensional space. We propose two types of hybrid nonlinear observers using continuous angular velocity and linear acceleration measurements as well as intermittent landmark position measurements. The first type relies on a fixed-gain design approach based on an infinite-dimensional optimization, while the second one relies on a variable-gain design approach based on a continuous-discrete Riccati equation. For each case, we provide two different observers with and without the estimation of the gravity vector. The proposed observers are shown to be exponentially stable with a large domain of attraction. Simulation and experimental results are presented to illustrate the performance of the proposed observers.