Satellite Attitude Estimation UKF Algorithm Based on Star-Sensor

2006 ◽  
Author(s):  
Hui Li ◽  
Zhao-wei Sun ◽  
Shi-jie Zhang
Keyword(s):  
Attitude Estimation ◽  
Star Sensor ◽  
Satellite Attitude

scholarly journals Evaluation of Murrell’s EKF-Based Attitude Estimation Algorithm for Exploiting Multiple Attitude Sensor Configurations

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6450
Author(s):  
Sharanabasaweshwara Asundi ◽  
Norman Fitz-Coy ◽  
Haniph Latchman
Keyword(s):  
Magnetic Field ◽  
Time Derivative ◽  
Estimation Algorithm ◽  
Field Vector ◽  
Attitude Estimation ◽  
Magnetic Field Vector ◽  
Sun Sensor ◽  
Satellite Attitude ◽  
Multiple Sensor ◽  
Sensor Suite

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.

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

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
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.

Configuration Estimation of Gough-Stewart Platforms Using Extended Kalman Filtering

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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