Research on Application of Antenna Measurement Information in Satellite Attitude Determination

Author(s):  
Xia Keqiang ◽  
Du Chunyan ◽  
Wang Baohua ◽  
Xing Meng ◽  
Feng Peiyong ◽  
...  
2021 ◽  
Author(s):  
Xia Keqiang ◽  
Wang Baohua ◽  
Du Chunyan ◽  
Xing Meng ◽  
Zhao Sheng ◽  
...  

1987 ◽  
Author(s):  
Robert L. Russell ◽  
Andrew J. D' Arcy

Author(s):  
Baojian Yang ◽  
Lu Cao ◽  
Dechao Ran ◽  
Bing Xiao

Due to unavoidable factors, heavy-tailed noise appears in satellite attitude estimation. Traditional Kalman filter is prone to performance degradation and even filtering divergence when facing non-Gaussian noise. The existing robust algorithms have limited accuracy. To improve the attitude determination accuracy under non-Gaussian noise, we use the centered error entropy (CEE) criterion to derive a new filter named centered error entropy Kalman filter (CEEKF). CEEKF is formed by maximizing the CEE cost function. In the CEEKF algorithm, the prior state values are transmitted the same as the classical Kalman filter, and the posterior states are calculated by the fixed-point iteration method. The CEE EKF (CEE-EKF) algorithm is also derived to improve filtering accuracy in the case of the nonlinear system. We also give the convergence conditions of the iteration algorithm and the computational complexity analysis of CEEKF. The results of the two simulation examples validate the robustness of the algorithm we presented.


2016 ◽  
Vol 16 (8) ◽  
pp. 2260-2271 ◽  
Author(s):  
Agustin Garcia Saez ◽  
Jose M. Quero ◽  
Manuel Angulo Jerez

2021 ◽  
Vol 2090 (1) ◽  
pp. 012116
Author(s):  
Angel Porras-Hermoso ◽  
Javier Cubas ◽  
Santiago Pindado

Abstract Attitude determination represents a fundamental task for most of the spacecrafts. It relies on three basic aspects: 1) sensors selection, 2) relevant environmental conditions estimation, and 3) algorithms that relate the sensor measurements to the expected conditions in the reference frame. Each one has its own impact on the accuracy that the system can achieve. Besides, two factors stand out above the others in terms of accuracy: 1) sensor quality (calibration, range, etc), and 2) precision of the environmental models. The computation of the satellite attitude needs at least two independent measurements (magnetometers, solar sensors...), whit their corresponding simulated measurements in the reference frame. Nevertheless, the number of measurements can be reduced to one if the satellite attitude is constrained. This paper describes a procedure to calculate satellites’ attitude and the main environmental models used (Earth magnetic model, Sun position model, Albedo model), including orbit propagation. This methodology can be extended to measure the performance of a sensor if the satellite attitude can be derived from other measurements and satellite constrains. The methodology is checked with data from the UPMSat-2 mission (launched in September 2020 within the VEGA VV16 mission). This is a 50-kg satellite designed and developed at the Universidad Politécnica de Madrid (UPM).


2012 ◽  
Vol 116 (1178) ◽  
pp. 373-389
Author(s):  
Y. Jiao ◽  
J. Wang ◽  
X. Pan ◽  
H. Zhou

Abstract The satellite attitude determination approach based on the Extended Kalman Filter (EKF) has been widely used in many real applications. However, the accuracy of this method largely depends on the fitness of measurement model. We aim to analyse the influence of measurement errors to the accuracy of EKF based attitude determination approach in this paper. The measurement errors, which are divided into structural error and nonstructural error by their influences, are analysed in principle. In the setting of the combination of star sensors and gyros, according to the property of innovation, we employ the technique of correlation test to analyse the influences of different kinds of measurement errors. Experimental results demonstrate the effectiveness of our previous analysis.


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