Robust Rendezvous Navigation in Elliptical Orbit

Karlgaard, Christopher D.

doi:10.2514/1.19148

Cited by 91 publications

(58 citation statements)

References 14 publications

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“…The covariance of the each process noise components w x , w y and w z are given by 10 − 4 m 2 /s 4 . The tuning parameter γ is set to 1.345 [4]. The weighting factor α is set to 0.2.…”

Section: Numerical Simulationsmentioning

confidence: 99%

Adaptive robust Kalman filter for relative navigation using global position system

Gong

Liu

et al. 2013

IET Radar, Sonar & Navigation

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An adaptive robust Kalman filter algorithm is derived to account for both process noise and measurement noise uncertainty. The adaptive algorithm estimates process noise covariance based on the recursive minimisation of the difference between residual covariance matrix given by the filter and that calculated from time-averaging of the residual sequence generated by the filter at each time step. A recursive algorithm is proposed based on both Massachusetts Institute of Technology (MIT) rule and typical non-linear extended Kalman filter equations for minimising the difference. The measurement update using a robust technique to minimise a criterion function originated from Huber filter. The proposed adaptive robust Kalman filter has been successfully implemented in relative navigation using global position system for spacecraft formation flying in low earth orbit, with real-orbit perturbations and non-Gaussian random measurement errors. The numerical simulation results indicate that the proposed adaptive robust filter can provide better relative navigation performance in terms of accuracy and robustness as compared with previous filter algorithms.

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“…The covariance of the each process noise components w x , w y and w z are given by 10 − 4 m 2 /s 4 . The tuning parameter γ is set to 1.345 [4]. The weighting factor α is set to 0.2.…”

Section: Numerical Simulationsmentioning

confidence: 99%

Adaptive robust Kalman filter for relative navigation using global position system

Gong

Liu

et al. 2013

IET Radar, Sonar & Navigation

View full text Add to dashboard Cite

show abstract

“…As far as we understand, however, most previous works (including [10][11][12]) based on the relative motion equations in the Hill frame have used purely mathematical approaches in synthesis of their control laws, and the physical properties of the relative motion have been overlooked. As Slotine and Li have mentioned in their works [14,15], some physical properties, such as energy conservation, may hold significant potential in analysis and control design for multiinput nonlinear mechanical systems.…”

Section: Introductionmentioning

confidence: 99%

“…The spherical coordinate version of Eq. (1) is also available in [11,18,19]. Equation (1) is a highly coupled (between x and z axes motions) multi-input multi-output dynamic equation.…”

Section: Relative Equations Of Motionmentioning

confidence: 99%

“…However, it used simple Clohessy-Wiltshire equations [13], which are valid only for a circular orbit and also uses the assumption that the deputy is on the chief's orbit plane. More recently, Karlgaard [11] proposed a continuous feedback controller for rendezvous navigation in elliptical orbit. In this work, the full equations of relative motion (see [9]) were converted into full nonlinear equations in a spherical coordinate system, and then a navigation control law was derived using the simple feedback linearization method.…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, a number of research works have been published which propose relative motion controls in orbits [4][5][6][7][8][9][10][11][12]. Some of them are focusing on the spacecraft formation flying problem of maintaining the relative orbit of a cluster of spacecraft [4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

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