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Three-axis attitude determination via Kalman filtering of magnetometer data

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TLDR
In this article, a three-axis magnetometer/Kalman filter attitude determination system for a spacecraft in low-altitude Earth orbit is developed, analyzed, and simulation tested, which can be used for attitude stabilization.
Abstract
A three-axis Magnetometer/Kalman Filter attitude determination system for a spacecraft in low-altitude Earth orbit is developed, analyzed, and simulation tested. The motivation for developing this system is to achieve light weight and low cost for an attitude determination system. The extended Kalman filter estimates the attitude, attitude rates, and constant disturbance torques. Accuracy near that of the International Geomagnetic Reference Field model is achieved. Covariance computation and simulation testing demonstrate the filter's accuracy. One test case, a gravity-gradient stabilized spacecraft with a pitch momentum wheel and a magnetically-anchored damper, is a real satellite on which this attitude determination system will be used. The application to a nadir pointing satellite and the estimation of disturbance torques represent the significant extensions contributed by this paper. Beyond its usefulness purely for attitude determination, this system could be used as part of a low-cost three-axis attitude stabilization system.

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Real-Time Attitude-Independent Three-Axis Magnetometer Calibration

TL;DR: In this article, the authors developed alternative real-time algorithms based on both the extended Kalman filter and unscented filter for three-axis magnetometer sensor calibration, which can now be performed on-orbit during typical spacecraft mission-mode operations.
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Accurate Attitude Estimation of a Moving Land Vehicle Using Low-Cost MEMS IMU Sensors

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References
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Book

Linear systems

Journal ArticleDOI

Kalman Filtering for Spacecraft Attitude Estimation

TL;DR: In this article, the authors present a review of the methods of Kalman filtering in attitude estimation and their development over the last two decades, focusing on three-axis gyros and attitude sensors.
Journal ArticleDOI

Attitude Determination from Vector Observations: Quaternion Estimation

TL;DR: In this paper, two recursive estimation algorithms, which use pairs of measured vectors to yield minimum variance estimates of the quaternion of rotation, are presented, and a variant of the extended Kalman filter is used to estimate the difference between the estimation and its estimate.
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