Adaptive Tuning of the Unscented Kalman Filter for Satellite Attitude Estimation
- 1 May 2015
- journal article
- research article
- Published by American Society of Civil Engineers (ASCE) in Journal of Aerospace Engineering
Abstract
Determining the process noise covariance of the unscented Kalman filter (UKF) is a difficult procedure. The analytical approximation method gives satisfactory results in certain cases, but it fails when generalized for the estimation of the extended states, such as the case that sensor biases or scale factors are included in the state vector. The main aim of this research is to find an appropriate tuning algorithm for the process noise covariance of the UKF when the magnetometer biases are estimated, as well as attitude and gyro biases. In this sense, an adaptive tuning method for an UKF that is used for satellite attitude estimation is given and the adaptive UKF algorithm is tested in various scenarios for the attitude and sensor bias estimation. The given adaptation method is an easy way of tuning the filter, especially in the absence of any analytical approximation for the calculation of the process noise covariance, and the performed simulations show that by using the adaptive UKF, it is possible to get accurate estimates that are close to optimal.Keywords
This publication has 12 references indexed in Scilit:
- Steady-State Accuracy Solutions of More Spacecraft Attitude EstimatorsPublished by American Institute of Aeronautics and Astronautics (AIAA) ,2011
- In-Orbit Magnetic Disturbance Estimation and Compensation Using UKF in Nano-Satellite MissionPublished by American Institute of Aeronautics and Astronautics (AIAA) ,2009
- Methods for Estimating State and Measurement Noise Covariance Matrices: Aspects and ComparisonIFAC Proceedings Volumes, 2009
- Adaptive Sigma Point Filtering for State and Parameter EstimationPublished by American Institute of Aeronautics and Astronautics (AIAA) ,2004
- Unscented Filtering for Spacecraft Attitude EstimationJournal of Guidance, Control, and Dynamics, 2003
- Demonstration of Adaptive Extended Kalman Filter for Low-Earth-Orbit Formation Estimation Using CDGPSNAVIGATION: Journal of the Institute of Navigation, 2003
- Analytic Steady-State Accuracy of a Spacecraft Attitude EstimatorJournal of Guidance, Control, and Dynamics, 2000
- A new method for the nonlinear transformation of means and covariances in filters and estimatorsIEEE Transactions on Automatic Control, 2000
- Adaptive Kalman Filtering for INS/GPSJournal of Geodesy, 1999
- Analytic Steady-State Accuracy Solutions for Two Common Spacecraft Attitude EstimatorsJournal of Guidance, Control, and Dynamics, 1978