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Method for Collision Avoidance in spacecraft Rendezvous Problems with space objects in a Phasing Orbit

Computer Modeling in Engineering & Sciences 2021年第6期127卷 977-991页

作者： Danhe Chen A.A.Baranov Chuangge Wang M.O.Karatunov N.Yu.Makarov Nanjing University of Science and Technology Nanjing210094China Keldysh Institute of Applied Mathematics Russian Academy of SciencesMoscowRussia Peoples’Friendship University of Russia(RUDN University) MoscowRussia

As the number of space objects(SO)increases,collision avoidance problem in the rendezvous tasks or reconstellation of satellites with SO has been paid more attention,and the dangerous area of a possible collision should be *** this paper,a maneuvering method is proposed for avoiding collision with a space debris object in the phasing orbit of the initial optimal ***,based on the plane of eccentricity vector components,relevant dangerous area which is bounded by two parallel lines is *** axises of eccentricity vector system pass through the end of eccentricity vector of phasing orbit in the optimal solution,and orientation of axis depends on the latitude argument where a collision will *** dangerous area is represented especially with the graphical dialogue,and it allows to find a compromise between the SO avoiding and the fuel consumption *** proposed method to solve the collision avoidance problem provides simplicity to calculate rendezvous maneuvers,and possibility to avoid collisions from several collisions or from“slow”collisions in a phasing orbit,when the protected spacecraft and the object fly dangerously close to each other for a long period.

关键词： spacecraft collision avoidance rendezvous problem space objects phasing orbit

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Re-Entry of space objects from Low Eccentricity Orbits

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International Journal of Astronomy and Astrophysics 2019年第3期9卷 200-216页

作者： Cynthia Sharon Lawrence Ram Krishan Sharma Department of Aerospace Engineering Karunya Institute of Technology and SciencesCoimbatoreIndia

This paper deals with the re-entry predictions of the space objects from the low eccentric orbit. Any re-entering object re-enters the Earth’s atmosphere with a high orbital velocity. Due to the aerodynamic heating the object tends to break into multiple fragments which later pose a great risk hazard to the population. Here a satellite is considered as the space object for which the re-entry prediction is made. This prediction is made with a package where the trajectory path, the time of re-entry and the survival rate of the fragments is done. The prediction is done using DRAMA 2.0—ESA’s Debris Risk Assessment and Mitigation Analysis Tool suite, MATLAB and Numerical Prediction of Orbital Events software. The predicted re-entry time of OSIRIS 3U was found to be on 7th March 2019, 7:25 (UTC), whereas the actual re-entry time was on 7th March 2019, 7:03 (UTC). The trajectory path found was 51.5699 deg. (Lat), −86.5738 deg. (Long.) with an altitude of 168.643 km. But the actual trajectory was 51.76 deg. (Lat), −89.01deg. (Long.) with an altitude of 143.5 km.

关键词： Re-Entry space objects Low Eccentricity Orbits DRAMA 2.0 Risk Event Statistics

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Comparison of Three Filters space objects Parameters Estimation via Astrometric and Photometric Data

Comparison of Three Filters Space Objects Parameters Estimat...

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第40届中国控制会议

作者： Lingwei Li Yiming Guo Xiwei Wu Cihang Wu Bing Xiao School of Automation Northwestern Polytechnical University

To ensure safety for in-orbital satellites, it is important to identify space objects. Therefore, the parameters estimation problem of space objects has attracted more and more research interests in aerospace engineering. The unscented Kalman filter（UKF） and the particle filter（PF） are two common estimation methods applied to solve this problem through nonlinear filtering techniques. However, UKF has the disadvantage of low estimation accuracy and divergence. The PF has a high computational cost when applied to estimate parameters of space objects. To solve those two drawbacks, the square root cubature Kalman filter（SRCKF） is applied, which can guarantee high estimation accuracy and robustness while still reducing the computational *** results are presented to compare those three filters’ parameter estimation performance of space objects. It is seen that the SRCKF achieves better estimation accuracy than the UKF. The SRCKF and the UKF have higher computational efficiency than the PF.

关键词： space objects Parameters estimation Nonlinear filters Astrometric data Photometric data

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