Multiplicative-modified-Rodrigues-parameters-based strong tracking unscented Kalman filter for satellite attitude estimation

Abstract In this paper, an improved strong tracking unscented Kalman filter (STUKF) based on multiplicative modified Rodrigues parameters (MRPs) is proposed for satellite attitude estimation. The multiplicative MRPs are superior to additive ones in terms of attitude representation, especially when attitude angles are large. By minimizing the loss function in Wahba’s problem, a novel method of weighted average for MRPs is derived to replace the simple procedure. The generation of Sigma points, update of state variables and calculation of covariance matrices are all different from the existing literature to maintain the multiplicative property of MRPs. Simulation results by raw telemetry data from the on-orbit CubeSat Enlai-1 demonstrate the excellent performance of the proposed filter under large attitude angles.

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Adaptive Tuning of the Unscented Kalman Filter for Satellite Attitude Estimation

Journal of Aerospace Engineering ◽

10.1061/(asce)as.1943-5525.0000412 ◽

2015 ◽

Vol 28 (3) ◽

pp. 04014088 ◽

Cited By ~ 9

Author(s):

Halil Ersin Soken ◽

Shin-ichiro Sakai

Keyword(s):

Kalman Filter ◽

Unscented Kalman Filter ◽

Attitude Estimation ◽

Adaptive Tuning ◽

Satellite Attitude

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Residual Based Adaptive Unscented Kalman Filter for Satellite Attitude Estimation

AIAA Guidance, Navigation, and Control Conference ◽

10.2514/6.2012-4476 ◽

2012 ◽

Cited By ~ 4

Author(s):

H. Ersin Soken ◽

Shin-ichiro Sakai

Keyword(s):

Kalman Filter ◽

Unscented Kalman Filter ◽

Attitude Estimation ◽

Satellite Attitude ◽

Adaptive Unscented Kalman Filter

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Improvement of Attitude Estimation Using Modified Rodrigues Parameters and Intelligent Controller

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.556-562.2279 ◽

2014 ◽

Vol 556-562 ◽

pp. 2279-2284

Author(s):

Qiang Liu ◽

Fu Yin Gao ◽

Chang Gang Wang ◽

Yu Han

Keyword(s):

Kalman Filter ◽

Computational Efficiency ◽

Fuzzy Controller ◽

Inertial Sensors ◽

Estimation Method ◽

Attitude Estimation ◽

State Variables ◽

Filter Model ◽

Modified Rodrigues Parameters ◽

Filter Tuning

The attitude estimation method of attitude heading reference system (AHRS) using an Extended Kalman Filter (EKF) with a filter tuning algorithm based on fuzzy controller is introduced.The AHRS uses inertial sensors and magnetometers to calculate its attitude. It is known that the attitude update using gyros are prone to diverge and hence the attitude error needs to compensate using accelerometers and magnetometers. In this paper, a Kalman filter model with a state variables represented by Modified Rodrigues Parameters (MRP) is presented to improve the computational efficiency and a model changing algorithm is used to make the filter more robust to acceleration and magnetic disturbances.If the AHRS measures any disturbances which are caused by movement of the vehicle, using fuzzy controller changes the filter gain .Simulation results show, EKF tuned by fuzzy controller is correct method that makes robust to disturbances more properly ,Rodrigues parameters can improve the computational efficiency..

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Comparative Analysis of Low Earth Orbit Satellite Attitude Determination using Sensor Integration and Attitude Estimation using Kalman Filter

INCAS BULLETIN ◽

10.13111/2066-8201.2021.13.2.12 ◽

2021 ◽

Vol 13 (2) ◽

pp. 117-132

Author(s):

M. RAJA

Keyword(s):

Kalman Filter ◽

Attitude Determination ◽

Unscented Kalman Filter ◽

Filter Design ◽

Attitude Estimation ◽

Matrix Form ◽

Convergence Time ◽

Linear Filters ◽

Satellite Attitude ◽

Non Linear

The objective of the research is to undergo a performance comparison in terms of accuracy, convergence time, amount of memory, etc. between the satellite attitude determination and attitude estimation using non-linear filters. The fundamental approach towards it is to design an OBC (On Board Computer) that would help in achieving a controlled output for the chosen plant (MicroMAS1 satellite). The attitude determination algorithm is implemented through TRIAD algorithm, which takes sensor readings of body frame and inertial frame of reference. Then it is used to determine the rotation matrix (DCM) by converting the matrix form into vector form and again back to matrix form to determine the 3x3 matrix, which includes all the Euler angle equations to determine the pitch, roll, yaw characteristics of the system. The attitude estimation algorithms involves the use of nonlinear filters which provide an added advantage that energy can be transferred in a designed manner and extra degrees of freedom are available in filter design. The Unscented Kalman Filter (UKF) is preferred as it addresses the problem using a deterministic sampling approach. Moreover, the non-linear filters are used to remove the noise error and disturbance caused by engine. The design of satellite attitude models involves more of a mathematical approach that would be dealt with MATLAB and SIMULINK operations.

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