Relative position and attitude estimation for satellite formation with coupled translational and rotational dynamics

Xing, Yuxiang; Cao, Xi‐Ren; Zhang, Shijie; Guo, Haibo; Wang, Feng

doi:10.1016/j.actaastro.2010.04.002

Cited by 63 publications

(35 citation statements)

References 17 publications

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“…Nowadays, vision-based navigation systems, which have the advantage of being entirely passive and of low power consumption, are usually used to determine the relative attitude and position [10,11]. The vision measurement has been separated into two aspects of model based and modelindependent methods [12].…”

Section: Introductionmentioning

confidence: 99%

Relative Attitude Estimation for a Uniform Motion and Slowly Rotating Noncooperative Spacecraft

Zhang

Liu

et al. 2017

Mathematical Problems in Engineering

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This paper presents a novel relative attitude estimation approach for a uniform motion and slowly rotating noncooperative spacecraft. It is assumed that the uniform motion and slowly rotating noncooperative chief spacecraft is in failure or out of control and there is no a priori rotation rate information. We utilize a very fast binary descriptor based on binary robust independent elementary features (BRIEF) to obtain the features of the target, which are rotational invariance and resistance to noise. And then, we propose a novel combination of single candidate random sample consensus (RANSAC) with extended Kalman filter (EKF) that makes use of the available prior probabilistic information from the EKF in the RANSAC model hypothesis stage. The advantage of this combination obviously reduces the sample size to only one, which results in large computational savings without the loss of accuracy. Experimental results from real image sequence of a real model target show that the relative angular error is about 3.5% and the mean angular velocity error is about 0.1 deg/s.

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Section: Introductionmentioning

confidence: 99%

Relative Attitude Estimation for a Uniform Motion and Slowly Rotating Noncooperative Spacecraft

Zhang

Liu

et al. 2017

Mathematical Problems in Engineering

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“…Presently, Vision-based Navigation (VISNAV) systems, consisting of an optical sensor combined with specific light sources (beacons), are usually used to determine the relative attitude and position within the range of a few hundred metres Kim et al, 2007;Xing et al, 2010;Tang et al, 2010). In order to determine the coupled attitude and position from the Line-Of-Sight (LOS) measurements, a Gaussian Least Squares Differential Correction (GLSDC) algorithm is usually used to provide a deterministic solution.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, it is necessary to adopt the state estimation method to design a navigation filter. At present, two types of navigation filters include the absolute navigation filter (Wodffinden and Geller, 2007;Schmidt et al, 2010;Hablani, 2009) and the relative navigation filter Kim et al, 2007;Xing et al, 2010;Junkins et al, 1999;Hablani et al, 2002). The absolute navigation system formulates the dynamics models of the two spacecraft in the inertial frame and acquires the relative motion parameters by computing the differences between two spacecraft.…”

Section: Introductionmentioning

confidence: 99%

“…In general, the known beacon locations are defined in the master's body frame, whereas the relative position vector between the master and slave spacecraft is expressed in its LVLH frame. In Alonso et al (2000), Kim et al (2007) and Xing et al (2010), a simplified assumption that the master body frame coincides with its LVLH frame is made to construct the LOS observations for convenience. Unfortunately, this assumption is not valid under all situations, or in some rigorous senses, it is only a special case.…”

Section: Introductionmentioning

confidence: 99%

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Unscented Kalman Filtering for Relative Spacecraft Attitude and Position Estimation

Zhang

Yang

et al. 2014

J. Navigation

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A novel relative spacecraft attitude and position estimation approach based on an Unscented Kalman Filter (UKF) is derived. The integrated sensor suite comprises the gyro sensors on each spacecraft and a vision-based navigation system on the slave spacecraft. In the traditional algorithm, an assumption that the master's body frame coincides with its Local Vertical Local Horizontal (LVLH) frame is made to construct the line-of-sight observations for convenience. To solve this problem, two relative quaternions that map the master's LVLH frame to the slave and master body frames are involved. The general relative equations of motion for eccentric orbits are used to describe the positional dynamics. The implementation equations for the UKF are derived. A modified version of the UKF is presented based on the averaging-quaternion algorithm. Simulation results indicate that the proposed filters provide more accurate estimates of relative attitude and position than the Extended Kalman Filter (EKF).2. Relative attitude and position. 3. Eccentric orbit. 4. Quaternion.

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“…Also, because the rotation and the translation are coupled, which means the relative linear motion between the two spacecraft depends on the angular motion, the position parameters can only be estimated when the attitude parameters are converged. 12,13 These researches designed two separated estimators, in which the position estimation is turned on when the attitude estimation is done. In this way, the attitude parameters estimation and the position parameters estimation cannot be conducted in the same time, which will decrease the estimation efficiency.…”

Section: Introductionmentioning

confidence: 99%

Adaptive pose and inertial parameters estimation of free-floating tumbling space objects using dual vector quaternions

Hou

Wang

et al. 2017

Advances in Mechanical Engineering

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The robust parameter estimation of unknown space objects is essential to the on-orbit servicing missions. Based on the adaptive filtering techniques along with the dual quaternions modeling methods for pose estimation, this article proposes a dual vector quaternions-based extended Kalman filter and a dual vector quaternions-based adaptive fading factors extended Kalman filter to estimate the parameters of a free-floating tumbling space target. Using the dual vector quaternions to model the kinematics and dynamics of the system, the representation of the model is concise and compact. Also, the translational and rotational coupled effects are considered. In addition, the estimation algorithm is designed by the innovation-based multiple adaptive fading factors. As a result, the dual vector quaternions-based adaptive fading factors extended Kalman filter is robust against the faulty measurements which may lead to divergence of the traditional extended Kalman filter. As far as the authors know, both the designed filters are the first pose and inertial parameters estimation algorithms based on dual vector quaternions, and the dual vector quaternions-based adaptive fading factors extended Kalman filter is the first robust dual vector quaternions-based parameters estimating method. Finally, the proposed dual vector quaternions-based extended Kalman filter and dual vector quaternions-based adaptive fading factors extended Kalman filter are validated by mathematical simulations, and the dual vector quaternions-based adaptive fading factors extended Kalman filter is compared with the dual vector quaternions-based extended Kalman filter to show its robust performances.

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Relative position and attitude estimation for satellite formation with coupled translational and rotational dynamics

Cited by 63 publications

References 17 publications

Relative Attitude Estimation for a Uniform Motion and Slowly Rotating Noncooperative Spacecraft

Relative Attitude Estimation for a Uniform Motion and Slowly Rotating Noncooperative Spacecraft

Unscented Kalman Filtering for Relative Spacecraft Attitude and Position Estimation

Adaptive pose and inertial parameters estimation of free-floating tumbling space objects using dual vector quaternions

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