LEO navigation augmentation constellation design with the multi-objective optimization approaches

作     者：Yi HAN Lei WANG Wenju FU Haitao ZHOU Tao LI Beizhen XU Ruizhi CHEN Yi HAN;Lei WANG;Wenju FU;Haitao ZHOU;Tao LI;Beizhen XU;Ruizhi CHEN

作者机构：State Key Laboratory of Information Engineering in SurveyingMapping and Remote SensingWuhan UniversityWuhan 430079China Collaborative Innovation Center for Geospatial TechnologyWuhan 430079China 

基　　金：the National Natural Science Foundation of China(Nos.41704002 91638203 41904038) 

出 版 物：《Chinese Journal of Aeronautics》 (中国航空学报（英文版）)

年 卷 期：2021年第34卷第4期

页      码：265-278页

摘      要：Low Earth Orbit(LEO)satellite for navigation augmentation applications can significantly reduce the precise positioning convergence time and attract increasing attention recently.A few LEO Navigation Augmentation(LEO-NA)constellations have been proposed,while corresponding constellation design methodologies have not been systematically *** LEO-NA constellation generally consists of a huge number of LEO satellites and it strives for multiple optimization *** is essentially different from the communication constellation or earth observing constellation design *** this study,we modeled the LEO-NA constellation design problem as a multi-objective optimization problem and solve this problem with the MultiObjective Particle Swarm Optimization(MOPSO)*** objectives are used to strive for the best tradeoff between the augmentation performance and deployment efficiency,namely the Position Dilution of Precision(PDOP),visible LEO satellites and the orbit altitude.A fuzzy set approach is used to select the final constellation from a set of Pareto optimal solutions given by the MOPSO *** evaluate the performance of the optimized constellation,we tested two constellations with 144 and 288 satellites and each constellation has three optimization schemes:the polar constellation,the single-layer constellation and the two-layer *** results indicate that the optimized two-layer constellation achieves the best global coverage and is followed by the single-layer *** MOPSO algorithm can help to improve the constellation design and is suitable for solving the LEO-NA constellation design problem.

主 题 词：LEO-augmented multi-GNSS LEO constellation design MOPSO Multi-objective optimization Orbit optimization 

学科分类：08[工学] 082501[082501] 0825[工学-环境科学与工程类] 

核心收录：

D　O　I：10.1016/j.cja.2020.09.005

馆 藏 号：203101690...