Transactions of Nanjing University of Aeronautics & Astronautics
Non-cooperative Space Target Estimation Algorithm Without Prior Information Dependence Based on Temporal Line of Sight Constraint
Author:
Affiliation:

1.College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, P. R. China;2.School of Environmental Science, Nanjing Xiaozhuang University,Nanjing 211171, P. R. China

Clc Number:

V19

Fund Project:

This work was supported in part by the National Natural Science Foundation of China (Nos. 42271448, 41701531), and the Key Laboratory of Land Satellite Remote Sensing Application, Ministry of Natural Resources of the People’s Republic of China (No.KLSMNR-G202317).

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    Abstract:

    Under single-satellite observation, the parameter estimation of the boost phase of high-precision space non-cooperative targets requires prior information. To improve the accuracy without prior information, we propose a parameter estimation model of the boost phase based on trajectory plane parametric cutting. The use of the plane passing through the geo-center and the cutting sequence line of sight (LOS) generates the trajectory-cutting plane. With the coefficient of the trajectory cutting plane directly used as the parameter to be estimated, a motion parameter estimation model in space non-cooperative targets is established, and the Gauss-Newton iteration method is used to solve the flight parameters. The experimental results show that the estimation algorithm proposed in this paper weakly relies on prior information and has higher estimation accuracy, providing a practical new idea and method for the parameter estimation of space non-cooperative targets under single-satellite warning.

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XIAO Hui, ZHU Chongrui, LIU Xinqi, YU Yifan, SHENG Qinghong, YANG Rui. Non-cooperative Space Target Estimation Algorithm Without Prior Information Dependence Based on Temporal Line of Sight Constraint[J]. Transactions of Nanjing University of Aeronautics & Astronautics,2024,(4):526-540

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History
  • Received:September 25,2023
  • Revised:May 29,2024
  • Adopted:
  • Online: August 25,2024
  • Published:

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