Noncooperative Rendezvous Using Angles-Only Optical Navigation: System Design and Flight Results

D’Amico, Simone; Ardaens, Jean-Sébastien; Gaias, Gabriella; Benninghoff, Heike; Schlepp, Benjamin; Jørgensen, John Leif

doi:10.2514/1.59236

Cited by 131 publications

(55 citation statements)

References 16 publications

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“…In these plots the black dots mark the model of Eqs. (21)-(23), whereas the gray ones denote the model previously employed in our works (Ardaens and D'Amico 2009;D'Amico et al 2012D'Amico et al , 2013.…”

Section: Numerical Validationmentioning

confidence: 99%

Model of $$J_2$$ J 2 perturbed satellite relative motion with time-varying differential drag

Gaias

Ardaens

Montenbruck

2015

Celest Mech Dyn Astr

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This work revisits the modeling of the relative motion between satellites flying in near-circular low-Earth-orbits. The motion is described through relative orbital elements and both Earth's oblateness and differential drag perturbations are addressed. With respect to the former formulation, the description of the J 2 effect is improved by including also the changes that this perturbation produces in both relative mean longitude and relative inclination vector during a drifting phase, when a non-vanishing relative semi-major axis is required. The second major improvement consists in a general empirical formulation to include the mean effects produced by non-conservative perturbations, such as the differential aerodynamic drag acceleration. As a result, in addition to the well-known actions on the relative semi-major axis and on the mean along-track separation, the model is able to reflect the mean variation of the relative eccentricity vector due to atmospheric density oscillations produced by day and night transitions.

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Section: Numerical Validationmentioning

confidence: 99%

Model of $$J_2$$ J 2 perturbed satellite relative motion with time-varying differential drag

Gaias

Ardaens

Montenbruck

2015

Celest Mech Dyn Astr

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“…The growing interest in vision-based autonomous rendezvous and docking has produced a series of experimental spacecraft in an attempt to develop rendezvous and proximity operations technology that would be 2 International Journal of Aerospace Engineering more appropriate for small satellite. PRISMA [15] is the only in-orbit test bed of angles-only navigation, OHB Sweden [16], CNES [17], and DLR [18] imitated uncooperative rendezvous using AON separately, but the uncertainty is accuracy known with GPS and RF. Besides, all the rendezvous processes are ground-in-loop control; real AON based autonomous uncooperative rendezvous needs to be further studied.…”

Section: Introductionmentioning

confidence: 99%

Time and Covariance Threshold Triggered Optimal Uncooperative Rendezvous Using Angles-Only Navigation

You

Wang

Paccolat

et al. 2017

International Journal of Aerospace Engineering

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A time and covariance threshold triggered optimal maneuver planning method is proposed for orbital rendezvous using angles-only navigation (AON). In the context of Yamanaka-Ankersen orbital relative motion equations, the square root unscented Kalman filter (SRUKF) AON algorithm is developed to compute the relative state estimations from a low-volume/mass, power saving, and lowcost optical/infrared camera's observations. Multi-impulsive Hill guidance law is employed in closed-loop linear covariance analysis model, based on which the quantitative relative position robustness and relative velocity robustness index are defined. By balancing fuel consumption, relative position robustness, and relative velocity robustness, we developed a time and covariance threshold triggered two-level optimal maneuver planning method, showing how these results correlate to past methods and missions and how they could potentially influence future ones. Numerical simulation proved that it is feasible to control the spacecraft with a two-line element-(TLE-) level uncertain, 34.6% of range, initial relative state to a 100 m v-bar relative station keeping point, at where the trajectory dispersion reduces to 3.5% of range, under a 30% data gap per revolution on account of the eclipse. Comparing with the traditional time triggered maneuver planning method, the final relative position accuracy is improved by one order and the relative trajectory robustness and collision probability are obviously improved and reduced, respectively.

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“…The expansion given by Eq. (14) contains the following main terms, namely, 1) the derivative of the azimuth and elevation angles with respect to the relative position in the camera frame δr c , 2) the absolute attitude of the sensor, that is, the rotation matrix from J2000 to the camera frame, 3) the rotation matrix from the RTN frame to the inertial frame, and 4) the derivatives of the relative position in the RTN frame δr RTN with respect to the relative orbital elements δα. The mapping between relative orbital elements and relative position in the orbital frame is given by the adopted linear model as [4,5] ∂δr RTN ∂δα…”

Section: Mathematical Descriptionmentioning

confidence: 97%

“…As a result, the simulations provide the typical navigation accuracy that is achievable through a specific maneuver profile under realistic operational conditions. The proposed navigation tool contributes to the preparation of the DLR/GSOC Advanced Rendezvous Demonstration using GPS and Optical Navigation (ARGON) experiment, which at the time of this writing was scheduled for the extended phase of the PRISMA mission [14].…”

Section: Introductionmentioning

confidence: 99%

Angles-Only Navigation to a Noncooperative Satellite Using Relative Orbital Elements

Gaias

D’Amico

Ardaens

2014

Journal of Guidance, Control, and Dynamics

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This work addresses the design and implementation of a prototype relative navigation tool that uses camera-based measurements collected by a servicer spacecraft to perform far-range rendezvous with a noncooperative client in low Earth orbit. The development serves the needs of future on-orbit servicing missions planned by the German Aerospace Center. The focus of the paper is on the design of the navigation algorithms and the assessment of the expected performance and robustness under real-world operational scenarios. The tool validation is accomplished through a high-fidelity simulation environment based on the Multi Satellite Simulator in combination with the experience gained from actual flight data from the GPS and camera systems onboard the Prototype Research Instruments and Space Mission Technology Advancement mission. Nomenclaturê A, A = matrices of the partials of the nonlinear dynamics equations for the complete linear time-varying system and its relative dynamics subpart a = semimajor axis of the servicer satellitê B, B = control input matrices for the complete linear timevarying system and its subpart b = biases vector of the relative orbit estimatê C, C = measurement sensitivity matrices for the complete linear time-varying system and its subpart e = eccentricity of the servicer satellite H = matrix of accumulated partials of measures with respect to the initial state i = inclination of the servicer satellite K = condition number of a matrix m i = ith merit function n = mean angular motion of the servicer satellite P = covariance matrix of the estimation state R y x = rotation matrix from frame x to y r = relative position vector between the servicer and client t = time u = mean argument of latitude of the servicer satellite u c = line-of-sight unit vector in camera frame v = relative velocity vector between the servicer and client W = covariance matrix of the measurements W o = observability Gramian of the linear time-varying systemÂ,Ĉ x = filter state vector y = linearly modeled measurements via sensitivity matrix z = modeled observations: couple of azimuth and elevation Δ•= finite variation of a quantity δα = nondimensional relative orbital elements set δe = nondimensional relative eccentricity vector δi = nondimensional relative inclination vector δλ = nondimensional relative mean longitude δ• = relative quantity ϵ = uncorrelated measurement errors ζ = true observations η = azimuth angle of line-of-sight unit vector from servicer to client θ = ascending node of the relative orbit κ = one pixel camera resolution in radians Λ = information matrix μ = Earth constant ξ = single measure to refer either to azimuth or to elevation angles σ = standard deviation of state and/or measurement errorŝ Φ, Φ, Φ b = state transition matrices for the complete system and its subparts ϕ = mean argument of latitude of the relative perigee ψ = elevation angle of line-of-sight unit vector from servicer to client Ω = right ascension of the ascending node of the servicer satellite ω = argument of perigee of the servicer s...

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Noncooperative Rendezvous Using Angles-Only Optical Navigation: System Design and Flight Results

Cited by 131 publications

References 16 publications

Model of $$J_2$$ J 2 perturbed satellite relative motion with time-varying differential drag

Model of $$J_2$$ J 2 perturbed satellite relative motion with time-varying differential drag

Time and Covariance Threshold Triggered Optimal Uncooperative Rendezvous Using Angles-Only Navigation

Angles-Only Navigation to a Noncooperative Satellite Using Relative Orbital Elements

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