In flight magnetometer calibration via unscented Kalman filter

Date

2011-09-01

Author

Söken, Halil Ersin

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

209
views

0
downloads

In this study an unscented Kalman filter (UKF) based algorithm for the estimation of magnetometer biases and scale factors is proposed as a part of the attitude estimation scheme of a small satellite. UKF estimates magnetometer biases and scale factors as well as six attitude parameters of the satellite. Differently from the existing algorithms, scale factors are not treated together with the other parameters as a part of the state vector; three scale factors are estimated via a newly proposed extension for the UKF. Proposed algorithm is simulated for attitude estimation of a pico satellite which has three magnetometers and three rate gyros as measurement sensors. Besides, effects of non-calibrated magnetometers on attitude determination are shown via supplementary simulations. © 2011 IEEE.

URI

https://hdl.handle.net/11511/69757

DOI

https://doi.org/10.1109/rast.2011.5966970

Collections

Department of Aerospace Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Reconfigurable UKF for in-flight magnetometer calibration and attitude parameter estimation Söken, Halil Ersin (2011-01-01) In this study a reconfigurable unscented Kalman filter (UKF) based algorithm for the estimation of magnetometer biases and scale factors is proposed as a part of the attitude estimation scheme of a pico satellite. Algorithm is composed of two stages; in first stage UKF estimates magnetometer biases and scale factors as well as six attitude parameters of the satellite. Differently from the existing algorithms, scale factors are not treated together with the other parameters as a part of the state vector; thr...
UKF-Based Reconfigurable Attitude Parameters Estimation and Magnetometer Calibration Söken, Halil Ersin (2012-07-01) A reconfigurable unscented Kalman filter (UKF)-based estimation algorithm for magnetometer biases and scale factors is proposed as a part of the attitude estimation scheme of a pico satellite. Unlike existing algorithms, in this paper, scale factors are not treated, together with other parameters, as part of the state vector; they are estimated separately. After satisfying the conditions of the proposed stopping rule for bias estimation, UKF reconfigures itself for estimation of attitude parameters alone.
In-flight calibration of pico satellite attitude sensors via unscented kalman filter Söken, Halil Ersin (Pleiades Publishing Ltd, 2011-07-01) In this paper an Unscented Kalman filter based procedure is proposed for the bias estimation of attitude sensors of a pico satellite. Three axis magnetometers and the rate gyros are used as attitude sensors. At the initial phase, biases of three orthogonally located magnetometers are estimated as well as the attitude and attitude rates of the satellite. During initial period after the orbit injection, gyro measurements are accepted as bias free, since the precise gyros are working accurately and the accumul...
Estimation of pico-satellite attitude dynamics and external torques via Unscented Kalman Filter Söken, Halil Ersin (FapUNIFESP (SciELO), 2014-01-01) In this study, an Unscented Kalman Filter (UKF) algorithm is designed for estimating the attitude of a picosatellite and the in-orbit external disturbance torques. The estimation vector is formed by the satellite's attitude, angular rates, and the unknown constant components of the external disturbance torques acting on the satellite. The gravity gradient torque, residual magnetic moment, sun radiation pressure and aerodynamic drag are all included in the estimated external disturbance torque vector. The sa...
Multiple target tracking with Gaussian mixture PHD filter using passive acoustic Doppler-only measurements Guldogan, Mehmet B.; Lindgren, David; Gustafsson, Fredrik; Habberstad, Hans; Orguner, Umut (null; 2012-09-12) In this paper, we present the performance of the Gaussian mixture probability hypothesis density (GM-PHD) filter in tracking multiple ground targets using a passive acoustic-sensor network. For this purpose, an experimental setup consisting of a network of microphones and a loudspeaker was prepared. Non-cooperative transmissions from a loudspeaker (i.e. illuminator of opportunity) are exploited by non-directional separately located microphones (i.e. Doppler measuring sensors). Experimental proof-of-concept ...

Citation Formats

H. E. Söken, “In flight magnetometer calibration via unscented Kalman filter,” 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/69757.