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Adaptive robust cubature Kalman filtering for satellite attitude estimation

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Chinese Journal of Aeronautics 2018年第4期31卷 806-819页

作者： Zhenbing QIU Huaming QIAN Guoqing WANG College of Automation Harbin Engineering University

This paper is concerned with the adaptive robust cubature Kalman filtering problem for the case that the dynamics model error and the measurement model error exist simultaneously in the satellite attitude estimation system. By using Hubel-based robust filtering methodology to correct the measurement covariance formulation of cubature Kalman filter, the proposed filtering algorithm could effectively suppress the measurement model error. To further enhance this effect and reduce the impact of the dynamics model error, two different adaptively robust filtering algorithms,one with the optimal adaptive factor based on the estimated covariance matrix of the predicted residuals and the other with multiple fading factors based on strong tracking algorithm, are developed and applied for the satellite attitude estimation. The quaternion is employed to represent the global attitude parameter, and three-dimensional generalized Rodrigues parameters are introduced to define the local attitude error. A multiplicative quaternion error is derived from the local attitude error to maintain quaternion normalization constraint in the filter. Simulation results indicate that the proposed novel algorithm could exhibit higher accuracy and faster convergence compared with the multiplicative extended Kalman filter, the unscented quaternion estimator, and the adaptive robust unscented Kalman filter.

关键词： attitude estimation Cubature Kalman filter Multiple fading factors Optimal adaptive factor Robust filtering

REKF and RUKF for pico satellite attitude estimation in the presence of measurement faults

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Journal of Systems Engineering and Electronics 2014年第2期25卷 288-297页

作者： Halil Ersin Sken Chingiz Hajiyev Department of Space and Astronautical Science The Graduate University for Advanced Studies (Sokendai) Aeronautics and Astronautics Faculty Istanbul Technical University

When a pico satellite is under normal operational condi- tions, whether it is extended or unscented, a conventional Kalman filter gives sufficiently good estimation results. However, if the measurements are not reliable because of any kind of malfunc- tions in the estimation system, the Kalman filter gives inaccurate results and diverges by time. This study compares two different robust Kalman filtering algorithms, robust extended Kalman filter （REKF） and robust unscented Kalman filter （RUKF）, for the case of measurement malfunctions. In both filters, by the use of de- fined variables named as the measurement noise scale factor, the faulty measurements are taken into the consideration with a small weight, and the estimations are corrected without affecting the characteristic of the accurate ones. The proposed robust Kalman filters are applied for the attitude estimation process of a pico satel- lite, and the results are compared.

关键词： pico satellite attitude estimation robust Kalman filter-ing extended Kalman filter (EKF) unscented Kalman filter (UKF).

Application of the sun line-of-sight vector in the optimal attitude estimation of deep-space probe

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Journal of Harbin Institute of Technology(New Series) 2011年第2期18卷 96-100页

作者：常晓华崔祜涛邵巍 Deep Space Exploration Research Center Harbin Institute of Technology Beijing Institute of Astronautical Systems Engineering

This paper proposed an optimal algorithm using the sun line-of-sight vector to improve the probe attitude estimation accuracy in deep-space ***,the elaborate analysis of the attitude estimation error from vector observations was done to demonstrate that the geometric relation between the reference vectors is an important factor which influences the accuracy of attitude ***,with introduction of the sun line-of-sight vector,the attitude quaternion obtained from the star-sensor was converted into a pair of mutually perpendicular reference vectors perpendicular to the sun *** normalized weights were calculated according to the accuracy of the ***,the optimal attitude estimation in the least squares sense was achieved with the quaternion estimation ***,the results of simulation demonstrated the validity of the proposed optimal algorithm based on the practical data of the Deep Impact mission.

关键词： sun line-of-sight vector attitude estimation deep-space probe

Interlaced attitude estimation for Spacecraft Using Vector Observations

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Guidance, Navigation and Control 2021年第3期1卷 140-153页

作者： Lubin Chang College of Electrical Engineering Naval University of EngineeringWuhan 430033P.R.China

This paper proposes an interlaced attitude estimation method for spacecraft using vector observations,which can simultaneously estimate the constant attitude at the very start and the attitude of the body frame relative to its initial *** arbitrary initial attitude,described by constant attitude at the very start,is determined using quaternion estimator which requires no prior *** multiplicative extended Kalman-lter(EKF)is competent for estimating the attitude of the body frame relative to its initial state since the initial value of this attitude is exactly *** simulation results show that the proposed algorithms could achieve better performance compared with the state-of-the-art algorithms even with extreme large initial ***,the computational burden is also much less than that of the advanced nonlinear attitude estimators.

关键词： attitude estimation multiplicative extenoded Kalman filter quater mion estimalot

Marginalized particle filter for spacecraft attitude estimation from vector measurements

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控制理论与应用（英文版） 2007年第1期5卷 60-66页

作者： Yaqiu LIU Xueyuan JIANG Guangfu MA School of Astronautics Harbin Institute of Technology Harbin Heilongjiang 150001 China Information and Computer Engineering College Northeast Forestry University Harbin Heilongjiang 150040 China

An algorithm based on the marginalized particle filters （MPF） is given in details in this paper to solve the spacecraft attitude estimation problem： attitude and gyro bias estimation using the biased gyro and vector observations. In this algorithm, by marginalizing out the state appearing linearly in the spacecraft model, the Kalman filter is associated with each particle in order to reduce the size of the state space and computational burden. The distribution of attitude vector is approximated by a set of particles and estimated using particle filter, while the estimation of gyro bias is obtained for each one of the attitude particles by applying the Kalman filter. The efficiency of this modified MPF estimator is verified through numerical simulation of a fully actuated rigid body. For comparison, unscented Kalman filter （UKF） is also used to gauge the performance of MPE The results presented in this paper clearly derfionstrate that the MPF is superior to UKF in coping with the nonlinear model.

关键词： attitude estimation Particle filter Spacecraft Nonlinear filter Quaternion

attitude estimation of the Multi-rotor UAV Based on Simplified Adaptive Kalman Filter Algorithm

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Attitude Estimation of the Multi-rotor UAV Based on Simplifi...

2015年中国智能自动化学术会议

作者： Xin Zhang Yue Bai Zhijun Xu Rijun Wang Changchun Institute of Optics Fine Mechanics and Physics Chinese Academy of Sciences University of Chinese Academy of Sciences School of Electrical and Information Technology Changchun Institute of Technology

A simplified and improved attitude estimation algorithm is put forward,for the problems from the multi-rotor UAV in noise statistical characteristics unknown and time-varying, vibration as the main disturbance source, and highfrequent dynamic changes of the attitude angles. A simplified adaptive Kalman filter algorithm is designed for multi-sensor information fusion. With the attitude angle variance of the real-time dynamic calculation by the gyro and the accelerometer, the system noise variance and the measurement noise variance are estimated, so as to solve the unknown about the noise statistical characteristics, and to prevent the filter divergence. The flight experiment shows that the algorithm can guarantee the accuracy and the stability of the attitude angle estimation. The rootmean-square errors of the pitch and roll angles which are estimated by the simplified algorithm are 2.922° and 1.713°. The accuracy of the algorithm can meet the demands for the autonomous flight of the multi-rotor UAV.

关键词： Multi-rotor UAV attitude estimation Adaptive Kalman filter Quaternion method

Multi-Rate Kalman Filter for UAV attitude estimation Based on Adaptive Disturbance Model

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Multi-Rate Kalman Filter for UAV Attitude Estimation Based o...

第43届中国控制会议

作者： Weibin Feng Caiqi Wang Shiqian Wu Qi Wu Hongsen Zhu School of Information Science and Engineering Wuhan University of Science and Technology School of Software and Internet of things Engineering Jiangxi University of Finance and Economics

attitude estimation is a pivotal issue in unmanned aerial vehicle(UAV) control *** to its high dynamics,the current attitude estimation methods suffer from drift and instability in dynamic *** this paper,multi-rate Kalman filter is proposed to estimate the attitude i.e.,roll and pitch of UAVs using an Inertial Measurement Unit(IMU) consisting of a threeaxis gyroscope and accelerometer,in conjunction with an optical flow *** mitigate the effects of external acceleration disturbances,a first-order Gauss-Markov process is employed to model the disturbances and combines it with a Kalman filter to eliminate the disturbances.A sigmoid function is introduced to map the relationship between the magnitude of the external disturbance and the model coefficient to achieve adaptive adjustment of the model ***,the differential information of the optical flow velocity is used as an additional observation,and a multi-rate Kalman filter is presented based on the different update frequencies of the observation *** estimated gravity acceleration is then used to calculate the attitude via the fast complementary filtering(FCF) *** results on STM32 microcontroller show that the proposed method can effectively improve the accuracy of attitude estimation and anti-interference ability of UAVs in motion state.

关键词： attitude estimation external acceleration disturbances multi-rate Kalman filter IMU optical flow

Performance improvement of attitude estimation via X-ray pulsar for the spin-stabilized spacecrafts

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Performance improvement of attitude estimation via X-ray pul...

第三届中国卫星导航学术年会

作者： Luo Nan 1,2 ,Xu Luping 1,2 1 School of Electronic Engineering, Xidian University, Xi’an 710071, China 2 Institute of Astronautics and Aeronautics, Xidian University, Xi’an 710071, China

The accurate attitude determination for spacecraft has always been a significant issue in deep-space mission. This paper describes an approach which improves the performance of attitude estimation using X-ray pulsar for spin-axis stabilized spacecraft. The imperfect alignment of sensor’s view axis with spin axis of spacecraft introduces modulation error to the light curve of photons emitted from the specified pulsar, which affects the outcome of the attitude estimation system. In order to reduce the effect of modulation to a minimum, the demodulation to observed pulsar’s light curve is derived in detail. The second order model and the parameter fit method are employed to estimate the spacecraft attitude by X-ray pulsar’s energy measurement. Numerical experiments are shown that precise attitude estimation can be obtained with this method.

关键词： pulsars spacecraft attitude estimation modulation

Iterated Unscented Kalman Filter for Spacecraft attitude estimation

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Iterated Unscented Kalman Filter for Spacecraft Attitude Est...

第37届中国控制会议

作者： Huaming Qian Zhenbing Qiu College of Automation Harbin Engineering University

In this paper, an iterated unscented quaternion estimator for spacecraft attitude estimation is proposed. A step length-varying iteration technique is incorporated into the unscented quaternion estimator and the corresponding termination condition is introduced to control the number of iterations and reduce the computational burden. The reference quaternion in the measurement update is redefined by the developed iteration technique. Simulation results demonstrate the superiority of the proposed new algorithm in comparison with the multiplicative extended Kalman filter, norm constraint Kalman filter and the unscented quaternion estimator under large initialization condition errors. It also shows that the proposed algorithm exhibits a faster convergence rate.

关键词： unscented quaternion estimator attitude estimation iteration technique reference quaternion