Satellite maneuver detection and estimation with radar survey observations

Porcelli, Lorenzo; Pastor, Alejandro Pérez; Cano, Alejandro; Escribano, Guillermo; Sanjurjo-Rivo, Manuel; Escobar, Diego A.; Lizia, P. Di

doi:10.1016/j.actaastro.2022.08.021

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…. , 𝑚 − 1} and 𝜏 𝑚 ≤ 𝑇 (7) where Δ𝑡 min defines a minimum time interval between measurements, and 𝑇 defines the overall time of the measurement period. In this work, a local optimal for 𝝉 is solved for using MATLAB's fmincon function starting from an initial guess for 𝝉 which evenly distributes the measurement times across the measurement period.…”

Section: Approachmentioning

confidence: 99%

“…Numerical methods that leverage the full position of the spacecraft have typically been focused on maneuver detection and characterization for uncooperative spacecraft rather than direct in-space thrust estimation for cooperative spacecraft, though many approaches are applicable to both problems. Maneuver detection can consist of monitoring the divergence of the measurement residuals for unmodeled maneuvers [5][6][7], comparing the predicted state between a filter and a smoother [8], or analyzing differences between two-line-element data and a predicted state [9,10]. After a maneuver has been detected, it can be characterized through an adaptive variable-state dimension filter with covariance inflation [5] or through a least-squares fit of possible maneuvers to the observed measurements [7].…”

Section: Introductionmentioning

confidence: 99%

“…Maneuver detection can consist of monitoring the divergence of the measurement residuals for unmodeled maneuvers [5][6][7], comparing the predicted state between a filter and a smoother [8], or analyzing differences between two-line-element data and a predicted state [9,10]. After a maneuver has been detected, it can be characterized through an adaptive variable-state dimension filter with covariance inflation [5] or through a least-squares fit of possible maneuvers to the observed measurements [7]. Multiple model approaches, where multiple filters that include or exclude potential maneuvers are run in parallel, can also be used to detect and characterize maneuvers [11,12].…”

Section: Introductionmentioning

confidence: 99%

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Optimized Measurement Timing for In-Space Thrust Inference

Jia-Richards

2024

AIAA SCITECH 2024 Forum

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This paper considers the problem of optimizing the measurement timing for direct in-space thrust inference when the propulsive acceleration is known to act in the along-track direction and can be represented by a piecewise-constant function. A linear measurement model, derived in prior work, is used to relate changes in the spacecraft's initial state as well as magnitude of the average atmospheric drag and propulsive accelerations to deviations in the spacecraft's position in the orbit plane from a known reference trajectory. The linear measurement model allows the posterior covariance of the propulsive acceleration magnitudes to be analytically calculated given a prior covariance, the measurement covariance, and the measurement times. The measurement times can then be numerically optimized in order to minimize the posterior covariance of the propulsive acceleration magnitudes. Example scenarios considered in this work show that the posterior marginal standard deviation of the propulsive acceleration magnitudes can be reduced by approximately 20% purely through the optimization of a fixed number of measurement times. The primary benefit of this work is for data-limited scenarios, where the number of measurements may be limited, or scenarios with finite sensor resources.

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Section: Approachmentioning

confidence: 99%