Development, Verification, and Analysis of a Small Satellite Thrust Determination Filter

Craft, Kyle J.; Hecht, Grant R.; Darling, Jacob E.; Pernicka, Henry J.

doi:10.2514/1.a35147

Cited by 5 publications

(4 citation statements)

References 14 publications

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“…and Σ𝜙 = (𝐼 𝑞+6 − 𝐾 𝐻) Σ𝜙 (24) where 𝐼 𝑞+6 is a (𝑞 + 6) × (𝑞 + 6) identity matrix and 𝐾 is the optimal Kalman gain calculated as…”

Section: Problem Statementmentioning

confidence: 99%

“…Methods that target maneuver detection for an uncooperative spacecraft that performs maneuvers at an unknown time [20,21] or when telemetry may not be available during the maneuver [22,23] often leverage filtering which limits the reconstruction of earlier portions of the propulsion system thrust and may not efficiently use all available information. As such, methods directly targeted at thrust estimation for cooperative spacecraft based on iterative batch filters [24] or the ensemble Kalman update [25] have also been analyzed and both show promising results.…”

Section: Introductionmentioning

confidence: 99%

“…Both Refs. [24] and [25] require the use of multiple numerical simulations of the spacecraft trajectory-either for each iteration of the batch filter [24] or to estimate the optimal Kalman gain with ensemble approaches [25]-which can be computationally expensive, especially for high-fidelity models. Instead, this paper takes a more analytical approach to the thrust inference problem where only a single simulation of the spacecraft trajectory is required as a reference for a linear update to the propulsive acceleration profile.…”

Section: Introductionmentioning

confidence: 99%

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Segmented Reconstruction of Low-Acceleration Orbital Maneuvers

Jia-Richards

2023

Journal of Guidance, Control, and Dynamics

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This paper considers the problem of inferring the acceleration acting on a spacecraft in a near-circular orbit around a large planetary body when the acceleration is known to act in the along-track direction. A segmented approach is analyzed where the acceleration profile over a given period of time is approximated as a piecewise-constant profile. Noisy measurements of the spacecraft’s position are collected throughout the acceleration profile, from which the constant acceleration for each segment of the piecewise-constant profile can be inferred. The primary contribution of this work is an analytical approximation for the sensitivity of each measurement with respect to the constant acceleration of each segment. The resulting analytically approximated sensitivity matrix enables an analytical reconstruction of the acceleration profile given a numerically simulated reference trajectory. Applications of the segmented approach for thrust inference for both discontinuous and continuous thrust profiles are demonstrated. In particular, the reconstruction of a simulated thruster degradation profile over the course of 60 h is shown.

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“…and Σ𝜙 = (𝐼 𝑞+6 − 𝐾 𝐻) Σ𝜙 (24) where 𝐼 𝑞+6 is a (𝑞 + 6) × (𝑞 + 6) identity matrix and 𝐾 is the optimal Kalman gain calculated as…”

Section: Problem Statementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Segmented Reconstruction of Low-Acceleration Orbital Maneuvers

Jia-Richards

2023

Journal of Guidance, Control, and Dynamics

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“…Recent developments on numerical methods for direct in-space thrust estimation with cooperative spacecraft have examined the use of least-squares batch filters [18] as well as the ensemble Kalman update [19], and the ensemble Kalman update approach has since been demonstrated on flight data for an iodine electric propulsion system [20]. While these numerical approaches enable direct in-space thrust estimation, the use of these numerical methods for optimization of the thrust estimation process is intractable.…”

Section: Introductionmentioning

confidence: 99%

Optimized Measurement Timing for In-Space Thrust Inference

Jia-Richards

2024

Journal of Guidance, Control, and Dynamics

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A method for direct in-space thrust estimation from low-acceleration orbital maneuvers

Jia-Richards,

Marzouk,

Lozano

2023

J Electr Propuls

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This paper presents a method for performing direct in-space thrust estimation for low-acceleration propulsion systems using measurements of the spacecraft’s position taken during an orbital maneuver. The method is based on the ensemble Kalman update which does not require linearization of the spacecraft dynamics nor does it require Gaussian distributions for parameter uncertainties and measurement noise, allowing for a more general approach to thrust estimation. In addition, modeling error, such as that caused by the truncation of a spherical-harmonics representation of the Earth’s gravitational field, can be explicitly accounted for by representing the error with Gaussian processes. Simulated experiments show that uncertainty in the propulsive acceleration magnitude on the order of 0.1 $$\mu$$ μ m/s$$^2$$ 2 (1$$\sigma$$ σ ) can be achieved at an orbit altitude of approximately 410 km with temporally-sparse measurements even in the presence of uncertain atmospheric drag, and Monte Carlo analysis demonstrates the consistency of the inference results. Trends in the estimate of the propulsive acceleration with the true acceleration value are explored empirically and theoretically in order to allow for generalization of the results. The outcome of this work is a systematic approach to direct in-space thrust estimation that can support the final steps of development for future in-space electric propulsion systems or the calibration of a thruster during a mission.

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Development, Verification, and Analysis of a Small Satellite Thrust Determination Filter

Cited by 5 publications

References 14 publications

Segmented Reconstruction of Low-Acceleration Orbital Maneuvers

Segmented Reconstruction of Low-Acceleration Orbital Maneuvers

Optimized Measurement Timing for In-Space Thrust Inference

A method for direct in-space thrust estimation from low-acceleration orbital maneuvers

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