Satellite Attitude Estimation Using SVD-Aided EKF with Simultaneous Process and Measurement Covariance Adaptation

Pico- and nano-satellites, due to their form factor and size, are limited in accommodating multiple or redundant attitude sensors. For such satellites, Murrell’s implementation of the extended Kalman filter (EKF) can be exploited to accommodate multiple sensor configurations from a set of non redundant attitude sensors. The paper describes such an implementation involving a sun sensor suite and a magnetometer as attitude sensors. The implementation exploits Murrell’s EKF to enable three sensor configurations, which can be operationally commanded, for satellite attitude estimation. Among the three attitude estimation schemes, (i) sun sensor suite and magnetometer, (ii) magnetic field vector and its time derivative and (iii) magnetic field vector, it is shown that the third configuration is better suited for attitude estimation in terms of precision and accuracy, but can consume more time to converge than the other two.

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Robust Adaptive Filter for Small Satellite Attitude Estimation Based on Magnetometer and Gyro

Abstract and Applied Analysis ◽

10.1155/2014/159149 ◽

2014 ◽

Vol 2014 ◽

pp. 1-7 ◽

Cited By ~ 4

Author(s):

Zhankui Zeng ◽

Shijie Zhang ◽

Yanjun Xing ◽

Xibin Cao

Keyword(s):

Kalman Filter ◽

Attitude Estimation ◽

Optimal Filtering ◽

System State ◽

Small Satellite ◽

Adaptive Kalman Filter ◽

Satellite Attitude ◽

Observational Noise ◽

Robust Adaptive ◽

The Impact

Based on magnetometer and gyro measurement, a sequential scheme is proposed to determine the orbit and attitude of small satellite simultaneously. In order to reduce the impact of orbital errors on attitude estimation, a robust adaptive Kalman filter is developed. It uses a scale factor and an adaptive factor, which are constructed by Huber function and innovation sequence, respectively, to adjust the covariance matrix of system state and observational noise, change the weights of predicted and measured parameters, get suitable Kalman filter gain and approximate optimal filtering results. Numerical simulations are carried out and the proposed filter is approved to be robust for the noise disturbance and parameter uncertainty and can provide higher accuracy attitude estimation.

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Effect of Observation Errors on Satellite Attitude Estimation

IEEE Transactions on Aerospace and Electronic Systems ◽

10.1109/taes.1972.309472 ◽

1972 ◽

Vol AES-8 (1) ◽

pp. 81-84

Author(s):

Robert Fischl ◽

James P. Mc Ilvaine

Keyword(s):

Attitude Estimation ◽

Satellite Attitude

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Robust Kalman Filtering with Single and Multiple Scale Factors for Small Satellite Attitude Estimation

Advances in Estimation, Navigation, and Spacecraft Control ◽

10.1007/978-3-662-44785-7_21 ◽

2015 ◽

pp. 391-411

Author(s):

Halil Ersin Soken ◽

Chingiz Hajiyev ◽

Shin-ichiro Sakai

Keyword(s):

Kalman Filtering ◽

Multiple Scale ◽

Attitude Estimation ◽

Small Satellite ◽

Satellite Attitude ◽

Scale Factors

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Configuration Estimation of Gough-Stewart Platforms Using Extended Kalman Filtering

Volume 7A: 26th Biennial Mechanisms and Robotics Conference ◽

10.1115/detc2000/mech-14067 ◽

2000 ◽

Author(s):

Ernest D. Fasse ◽

Albert J. Wavering

Keyword(s):

Real Time ◽

Kalman Filtering ◽

Time Estimation ◽

Stewart Platform ◽

Attitude Estimation ◽

Extended Kalman Filtering ◽

Filtering Algorithms ◽

Satellite Attitude ◽

Deterministic Methods ◽

Real Time Estimation

Abstract This paper develops extended Kalman filtering algorithms for a generic Gough-Stewart platform assuming realistically available sensors such as length sensors, rate gyroscopes, and accelerometers. The basic idea is to extend existing methods for satellite attitude estimation. The nondeterministic methods are meant to be a practical alternative to existing iterative, deterministic methods for real-time estimation of platform configuration.

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