Inertial Properties Estimation of a Passive On-orbit Object Using Polhode Analysis

Setterfield, Timothy P.; Miller, David W.; Saenz-Otero, Alvar; Leonard, John J.

doi:10.2514/1.g003394

Cited by 25 publications

(22 citation statements)

References 8 publications

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“…A, B and C are the principal moments of inertia, H and L are the angular kinetic energy and angular momentum of space debris, ω s,M is the s-axis angular velocity projection int the frame M. Equations ( 3) and ( 4) show that the angular velocity vector's end moves at the intersection of the above two ellipsoids, and the projection of the angular velocity under the body-fixed frame is called polhode. According to the modeling method in [12], comparing the magnitudes of 2TB and L 2 and whether the mass distribution is symmetrical, the motions of space debris are classified into seven cases by Setterfield. Most space debris exhibit asymmetric mass distribution due to impact, and in the seven cases, the most common form of space debris is shown as Figure 2: In these forms, the elliptic functions become the aperiodic hyperbolic equations of the medium energy case [12], which means this form is the most unstable and unlikely motion.…”

Section: Coordinate Systems and Dynamic Model Of Space Debrismentioning

confidence: 99%

“…According to the modeling method in [12], comparing the magnitudes of 2TB and L 2 and whether the mass distribution is symmetrical, the motions of space debris are classified into seven cases by Setterfield. Most space debris exhibit asymmetric mass distribution due to impact, and in the seven cases, the most common form of space debris is shown as Figure 2: In these forms, the elliptic functions become the aperiodic hyperbolic equations of the medium energy case [12], which means this form is the most unstable and unlikely motion. Furthermore, the high energy case will decay to the low energy case because of energy dissipation.…”

Section: Coordinate Systems and Dynamic Model Of Space Debrismentioning

confidence: 99%

“…So, normalization is used to quantify inertia tensor. This normalization was also used by many visual measurement methods [11][12][13][14]. Setterfield et al [11,12] described a procedure of estimating the inertial properties based on stereo vision, and also used Euler-Poinsot to model the rotation of space debris.…”

Section: Introductionmentioning

confidence: 99%

“…This normalization was also used by many visual measurement methods [11][12][13][14]. Setterfield et al [11,12] described a procedure of estimating the inertial properties based on stereo vision, and also used Euler-Poinsot to model the rotation of space debris. By considering the relative magnitude of angular momentum and angular kinetic energy, as well as the relative situation of the principal moment of inertia, the motion was divided into seven forms, and two most common cases were considered.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Dynamic Parameter Estimation of Large Space Debris Based on Inertial and Visual Data Fusion

et al. 2021

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Most large space debris has large residual angular momentum, and the de-tumbling and capturing operation can easily cause instability and failure of tracking satellites. Therefore, it is necessary to perform real-time dynamic parameter identification of space debris prior to the imminent de-tumbling and capture operation, thus improving the efficiency and success of active debris removal (ADR) missions. A method for identifying dynamic parameters based on the fusion of visual and inertial data is proposed. To obtain the inertial data, the inertial measurement units (IMU) with light markers were fixed on the debris surface by space harpoon, which has been experimentally proven in space, and the binocular vision was placed at the front of a tracking satellite to obtain coordinates of the light markers. A novel method for denoising inertial data is proposed, which will eliminate the interference from the space environment. Furthermore, based on the denoised data and coordinates of the light markers, the mass-center location is estimated. The normalized angular momentum is calculated using the Euler–Poinsot motion characteristics, and all active debris removal parameters are determined. Simulations with Gaussian noise and experiments in the controlled laboratory have been conducted, the results indicate that this method can provide accurate dynamic parameters for the ADR mission.

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Section: Coordinate Systems and Dynamic Model Of Space Debrismentioning

confidence: 99%

Section: Coordinate Systems and Dynamic Model Of Space Debrismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Dynamic Parameter Estimation of Large Space Debris Based on Inertial and Visual Data Fusion

et al. 2021

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“…In all these methods, only normalized moments of inertia were estimated, since no external torques were applied on the target spacecraft. Setterfield et al [84] proposed a method to additionally estimate the three principal axes together with the inertia ratios through the analysis of the target object's polhode in an arbitrary target-fixed geometric frame. Felicetti et al [85] analyzed the estimation of the full inertia matrix by exerting a control torque on the object and by adopting an EKF.…”

Section: Design and Validation Of Monocular Navigation Systems: Partially Known Targetsmentioning

confidence: 99%

Review of the robustness and applicability of monocular pose estimation systems for relative navigation with an uncooperative spacecraft

Cassinis

Fonod

Gill

2019

Progress in Aerospace Sciences

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The relative pose estimation of an inactive target by an active servicer spacecraft is a critical task in the design of current and planned space missions, due to its relevance for close-proximity operations, i.e. the rendezvous with a space debris and/or in-orbit servicing. Pose estimation systems based solely on a monocular camera are recently becoming an attractive alternative to systems based on active sensors or stereo cameras, due to their reduced mass, power consumption and system complexity. In this framework, a review of the robustness and applicability of monocular systems for the pose estimation of an uncooperative spacecraft is provided. Special focus is put on the advantages of multispectral monocular systems as well as on the improved robustness of novel image processing schemes and pose estimation solvers. The limitations and drawbacks of the validation of current pose estimation schemes with synthetic images are further discussed, together with the critical trade-offs for the selection of visual-based navigation filters. The state-of-the-art techniques are analyzed in order to provide an insight into the limitations involved under adverse illumination and orbit scenarios, high image contrast, background noise, and low signal-to-noise ratio, which characterize actual space imagery, and which could jeopardize the image processing algorithms and affect the pose estimation accuracy as well as the navigation filter's robustness. Specifically, a comparative

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An introductory review of swarm technology for spacecraft on‐orbit servicing

Asri,

Zhu

2024

Int Journal of Mech Sys Dyn

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This review paper presents a comprehensive evaluation and forward‐looking perspective on the underexplored topic of servicing target objects using spacecraft swarms. Such targets can be known or unknown, cooperative or uncooperative, and pose significant challenges in modern space operations due to their inherent complexity and unpredictability. Successfully servicing space objects is vital for active debris removal and broader on‐orbit servicing tasks such as satellite maintenance, repair, refueling, orbital assembly, and construction. Significant effort has been invested in the literature to explore the servicing of targets using a single spacecraft. Given its advantages and benefits, this paper expands the discussion to encompass a swarm approach to the problem. This review covers various single‐spacecraft approaches and presents a critical examination of the existing, although limited, body of work dedicated to servicing orbital objects using multiple spacecraft. The focus is also broadened to include some influential studies concerning the characterization, capture, and manipulation of physical objects by general multiagent systems, a subject with significant parallels to the core interest of this manuscript. Furthermore, this article also delves into the realm of simultaneous localization and mapping, highlighting its application within close‐proximity operations in space, especially when dealing with unknown uncooperative targets. Special attention is paid to the benefits that this field can receive from distributed multiagent architectures. Finally, an exploration of the promising field of swarm robotics is presented, with an emphasis on its potential to revolutionize the servicing of orbital target objects. Concurrently, a survey of general research directly engaging swarms in the orbital context is conducted. This review aims to bridge the knowledge gap and stimulate further research in the underexplored domain of servicing space targets with spacecraft swarms.

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Inertial Properties Estimation of a Passive On-orbit Object Using Polhode Analysis

Cited by 25 publications

References 8 publications

Dynamic Parameter Estimation of Large Space Debris Based on Inertial and Visual Data Fusion

Dynamic Parameter Estimation of Large Space Debris Based on Inertial and Visual Data Fusion

Review of the robustness and applicability of monocular pose estimation systems for relative navigation with an uncooperative spacecraft

An introductory review of swarm technology for spacecraft on‐orbit servicing

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