Determination of relative motion of a space object from simultaneous measurements of range and range rate

Sanyal, Amit K.; Izadi, Maziar; Butcher, Eric A.

doi:10.1109/acc.2014.6858662

Cited by 13 publications

(16 citation statements)

References 13 publications

(20 reference statements)

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“…where ϑ j ∈ R 3 is the additive error in relative velocity measurement v m j . Instantaneous angular and translational velocity determination from such measurements is treated in Sanyal et al (2014a). As v j =ȧ j indicates, relative velocities of at least three points on O are needed to determine its relative translational and angular velocities uniquely at each instant.…”

Section: The Measurement Model For Velocities Ismentioning

confidence: 99%

“…where W = diag(w j ) ∈ R n×n is a positive diagonal matrix of weight factors for the measured e m j and the relative position potential function 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 The total potential function is defined as the sum of a generalized form of (63) used in Izadi and Sanyal (2014); Sanyal et al (2014a) for attitude determination on SO(3), and the translational potential (64) as…”

Section: Dynamic Estimation Of Relative Motion From Proximity Measurementioning

confidence: 99%

See 1 more Smart Citation

Coupled orbit–attitude dynamics and relative state estimation of spacecraft near small Solar System bodies

Misra

Izadi

Sanyal

et al. 2016

Advances in Space Research

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The effects of dynamical coupling between the rotational (attitude) and translational (orbital) motion of spacecraft near small Solar System bodies is investigated. This coupling arises due to the weak gravity of these bodies, as well as solar radiation pressure. The traditional approach assumes a pointmass spacecraft model to describe the translational motion of the spacecraft, while the attitude motion is considered to be completely decoupled from the translational motion. The model used here to describe the rigid-body spacecraft dynamics includes the non-uniform rotating gravity field of the small body up to second degree and order along with the attitude dependent terms, solar tide, and solar radiation pressure. This model shows that the second degree and order gravity terms due to the small body affect the dynamics of the spacecraft to the same extent as the orbit-attitude coupling due to the primary gravity (zeroth order) term. Variational integrators are used to simulate the dynamics of both the rigid spacecraft and the point mass. The small bodies considered here are modeled after Near-Earth Objects (NEO) Itokawa, and are assumed to be triaxial ellipsoids with uniform density. Differences in the numerically obtained trajectories of a rigid spacecraft and a point mass are then compared, to illustrate the impact of the orbit-attitude coupling on spacecraft dynamics in proximity of small bodies. Possible implications on the performance of model-based spacecraft control and on the station-keeping budget, if the orbit-attitude coupling is not accounted for in the model of the dynamics, are also discussed. An almost globally asymptotically stable motion estimation scheme based solely on visual/optical feedback that estimates the relative motion of the asteroid with respect to the spacecraft is also obtained. This estimation scheme does not require a model of the dynamics of the asteroid, which makes it perfectly suited for asteroids whose properties are not well known.

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Section: The Measurement Model For Velocities Ismentioning

confidence: 99%

Section: Dynamic Estimation Of Relative Motion From Proximity Measurementioning

confidence: 99%

Coupled orbit–attitude dynamics and relative state estimation of spacecraft near small Solar System bodies

Misra

Izadi

Sanyal

et al. 2016

Advances in Space Research

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“…Instantaneous angular and translational velocity determination from such measurements is treated in [26]. Note that v j =ȧ j , for j ∈ {1, 2, .…”

Section: Relative Velocities Measurement Modelmentioning

confidence: 99%

“…Therefore, the total potential function is defined as the sum of the generalization of (16) defined in [11], [26] for attitude determination on SO(3), and the translational energy (17) as…”

Section: A Lagrangian From Measurement Residualsmentioning

confidence: 99%

GPS-denied relative motion estimation for fixed-wing UAV using the variational pose estimator

Izadi

Sanyal

Beard

et al. 2015

2015 54th IEEE Conference on Decision and Control (CDC)

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Abstract-Relative pose estimation between fixed-wing unmanned aerial vehicles (UAVs) is treated using a stable and robust estimation scheme. The motivating application of this scheme is that of "handoff" of an object being tracked from one fixed-wing UAV to another in a team of UAVs, using onboard sensors in a GPS-denied environment. This estimation scheme uses optical measurements from cameras onboard a vehicle, to estimate both the relative pose and relative velocities of another vehicle or target object. It is obtained by applying the Lagrange-d'Alembert principle to a Lagrangian constructed from measurement residuals using only the optical measurements. This nonlinear pose estimation scheme is discretized for computer implementation using the discrete Lagranged'Alembert principle, with a discrete-time linear filter for obtaining relative velocity estimates from optical measurements. Computer simulations depict the stability and robustness of this estimator to noisy measurements and uncertainties in initial relative pose and velocities.

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“…where ϑ j ∈ R 3 is the additive error in velocity measurement v m j . Instantaneous angular and translational velocity determination from such measurements is treated in [26]. Note that v j = ȧj , for j ∈ {1, 2, .…”

Section: Relative Velocities Measurement Modelmentioning

confidence: 99%

GPS-Denied Relative Motion Estimation For Fixed-Wing UAV Using the Variational Pose Estimator

Izadi¹,

Sanyal²,

Beard³

et al. 2015

Preprint

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Relative pose estimation between fixed-wing unmanned aerial vehicles (UAVs) is treated using a stable and robust estimation scheme. The motivating application of this scheme is that of "handoff" of an object being tracked from one fixed-wing UAV to another in a team of UAVs, using onboard sensors in a GPS-denied environment. This estimation scheme uses optical measurements from cameras onboard a vehicle, to estimate both the relative pose and relative velocities of another vehicle or target object. It is obtained by applying the Lagrange-d'Alembert principle to a Lagrangian constructed from measurement residuals using only the optical measurements. This nonlinear pose estimation scheme is discretized for computer implementation using the discrete Lagranged'Alembert principle, with a discrete-time linear filter for obtaining relative velocity estimates from optical measurements. Computer simulations depict the stability and robustness of this estimator to noisy measurements and uncertainties in initial relative pose and velocities.

show abstract

Determination of relative motion of a space object from simultaneous measurements of range and range rate

Cited by 13 publications

References 13 publications

Coupled orbit–attitude dynamics and relative state estimation of spacecraft near small Solar System bodies

Coupled orbit–attitude dynamics and relative state estimation of spacecraft near small Solar System bodies

GPS-denied relative motion estimation for fixed-wing UAV using the variational pose estimator

GPS-Denied Relative Motion Estimation For Fixed-Wing UAV Using the Variational Pose Estimator

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