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面向低空无人机运行的高精度卫星测速算法

吉莉 孙蕊

西华大学学报(自然科学版)2024,Vol.43Issue(1):16-21,27,7.
西华大学学报(自然科学版)2024,Vol.43Issue(1):16-21,27,7.DOI:10.12198/j.issn.1673-159X.5184

面向低空无人机运行的高精度卫星测速算法

An Algorithm of High-precise Satellite Speed Prediction for UAV Operations in Low-air Space

吉莉 1孙蕊1

作者信息

  • 1. 南京航空航天大学海上智能网信技术教育部重点实验室,江苏南京 211106||南京航空航天大学空中交通管理系统全国重点实验室,江苏南京 211106
  • 折叠

摘要

Abstract

To solve the problem of poor accuracy of satellite-based navigation velocity estimation caused by multi-path error when UAVs operate in urban low altitude environment,this paper presents an optimization velocity estimation algorithm based on satellite azimuth weighting and doppler observation.The algorithm combines the advantages of doppler and carrier phase observations,and constructs a weighted model based on satellite azimuth angle according to the characteristics of the low-altitude operat-ing environment of the UAV,which effectively weakens the influence of multi-path effect on velocity es-timation accuracy,and improves the robustness of velocity estimation through the robust Kalman filter.The algorithm evaluation results based on the measured data show that in different scenarios,the velocity estim-ation accuracy of the proposed algorithm is improved by 32.23%,10.37%,50.39%and 10.20%,30.19%,31.54%,respectively in the three-dimensional of velocity direction compared under two scenes with the tra-ditional epoch differential carrier phase metho,which proves the effectiveness of the algorithm.

关键词

北斗卫星导航系统/无人机导航/卫星测速/加权最小二乘/抗差卡尔曼滤波

Key words

Beidou satellite navigation system(BDS)/UAV navigation/satellite velocity determination/weighted least squares/robust Kalman filtering

分类

天文与地球科学

引用本文复制引用

吉莉,孙蕊..面向低空无人机运行的高精度卫星测速算法[J].西华大学学报(自然科学版),2024,43(1):16-21,27,7.

基金项目

国家自然科学基金项目(42222401、42174025、41974033) (42222401、42174025、41974033)

工信部专项科研项目(TC220A04A-79) (TC220A04A-79)

江苏省"六大人才高峰"项目(KTHY-014) (KTHY-014)

江苏省自然科学基金项目(BK20211569) (BK20211569)

中央高校基本科研业务费专项资金项目(xcxjh20220726). (xcxjh20220726)

西华大学学报(自然科学版)

OACSTPCD

1673-159X

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