Welcome to Journal of University of Chinese Academy of Sciences,Today is

Journal of University of Chinese Academy of Sciences

Previous Articles     Next Articles

Single satellite Doppler localization method based on improved grid search

LIAO Jing1,2,4, LI Guotong1,2,3,4, HUANG Chenguang1,3,4, WANG Haiwang4, CHANG Jiachao4, XIAO Yang4   

  1. 1 Innovation Academy for Microsatellites, Chinese Academy of Sciences, Shanghai 201210, China;
    2 School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China;
    3 University of Chinese Academy of Sciences, Beijing 100049, China;
    4 Shanghai Spacesail Technologies Co., Ltd, Shanghai 201600, China
  • Received:2026-03-03 Revised:2026-05-18 Online:2026-05-18

Abstract: With the rapid development of low Earth orbit satellite technology, Doppler-based positioning has become a new research hotspot due to its significant advantages. In the single-satellite Doppler positioning scenario of low Earth orbit, due to the problems of positioning ambiguity and insufficient positioning accuracy in the traditional search method, this paper proposes a single-satellite Doppler positioning method based on improved grid search. In the coarse search stage, this method utilizes the geometric relationship between the satellite and the terminal to eliminate the ambiguous solutions in the traditional method without relying on any prior information; in the fine search stage, the density-based spatial clustering of applications with noise (DBSCAN) is introduced to analyze and process the candidate points, and weighted fusion technology is used to optimize the candidate points, thereby reducing the influence of outliers and improving positioning accuracy and robustness. Through the on-orbit measured data of the Spacesail constellation, it is verified that this algorithm can improve the positioning accuracy to within hundreds of meters compared to the traditional algorithm under similar complexity conditions.

Key words: low earth orbit satellite, Doppler positioning, grid search, cluster analysis

CLC Number: