基于电离层延迟智能估计的完好性评估

中国民航大学学报 ›› 2025, Vol. 43 ›› Issue (1): 53-59.

基于电离层延迟智能估计的完好性评估

卢丹，张宏健，钟伦珑，胡铁乔

中国民航大学电子信息与自动化学院，天津 300300

收稿日期:2023-03-29 修回日期:2023-06-01 出版日期:2025-04-09 发布日期:2025-04-09
作者简介:卢丹（1978— ），女，辽宁营口人，副教授，博士，研究方向为阵列信号处理、卫星导航
基金资助:
国家重点研发计划项目（2020YFB0505603）

Integrity evaluation based on intelligent estimation of ionospheric delay

LU Dan, ZHANG Hongjian, ZHONG Lunlong, HU Tieqiao

College of Electronic Information and Automation, CAUC, Tianjin 300300, China

Received:2023-03-29 Revised:2023-06-01 Online:2025-04-09 Published:2025-04-09

摘要/Abstract

摘要：

完好性是民用航空导航系统的性能要求之一，而电离层延迟是进行完好性评估的重要误差来源之一。对于

单频系统来说，通常采用 Klobuchar 模型对单频信号进行修正，但修正率仅为 60%左右，精度有限。本文提

出一种估算电离层延迟并将其用于完好性评估的方法，首先，通过反向传播（BP， back propagation）神经网

络对观测站电离层延迟进行训练，得到观测站的 BP 神经网络模型并计算电离层延迟，提高了观测站的电

离层延迟修正率；其次，利用经过训练的观测站 BP 神经网络模型以及三点插值法计算装备单频接收机的

航空器在其飞行位置的电离层延迟并进行完好性评估。以 2015 年 2—3 月的数据为例进行评估，结果表

明，通过 BP 神经网络模型以及三点插值法计算部分地区的电离层延迟与 Klobuchar 模型相比，计算电离层

延迟效果较好，提高了日间和夜间电离层延迟的修正率，从而提高了保护级的精度。

关键词:

电离层延迟, 完好性评估, Klobuchar 模型, BP 神经网络, 保护级

Abstract:

Integrity is one of the performance requirements of civil aviation navigation systems, and ionospheric delay is an

important error source for integrity evaluation. For the single-frequency system, Klobuchar model is usually used

to correct the single-frequency signal, but the correction rate is only about 60%, and the accuracy is limited. This

paper proposes a method for estimating ionospheric delay and using it for integrity evaluation. Firstly, the ionospheric delay of observation station is trained by back propagation (BP) neural network, and the ionospheric delay

is calculated by BP neural network model of the observation station, which improves the ionospheric delay correction rate of the observation station. Secondly, the ionospheric delay of the aircraft equipped with single-frequency

receiver at its flight position is calculated by using the trained observation station BP neural network model and the

three-point interpolation method, and the integrity evaluation is carried out. Evaluation based on the data from

February to March 2015 shows that, when calculating the ionospheric delay, the BP neural network model and the

three-point interpolation method perform better than the Klobuchar model in some areas. They improve the correction rates of ionospheric delay during both daytime and nighttime, thus enhancing the accuracy of the protection level.

Key words:

ionospheric delay, integrity evaluation, Klobuchar model, BP neural network, protection level

中图分类号:

P228

卢丹, 张宏健, 钟伦珑, 胡铁乔.

基于电离层延迟智能估计的完好性评估

[J]. 中国民航大学学报, 2025, 43(1): 53-59.

LU Dan, ZHANG Hongjian, ZHONG Lunlong, HU Tieqiao.

Integrity evaluation based on intelligent estimation of ionospheric delay

[J]. Journal of Civil Aviation University of China, 2025, 43(1): 53-59.

参考文献 14

	[1]
	ELLIOTT D K, CHRISTOPHER J H. Understanding GPS: principles
	and applications[M]. 2nd Edition. Beijing: Publishing House of Electronics Industry, 2007: 230-233.
[2]	牛飞. GNSS 完好性增强理论与方法研究[D]. 郑州: 解放军信息工
	程大学, 2008.
[3]	杨林, 吴德伟, 卢虎, 等. GNSS 组合系统用户完好性监测保护
	门限算法研究[J]. 电光与控制, 2014, 21(10): 61-64.
[4]	王雪艳, 李俊敏. 基于 RAIM 算法的 GNSS 完好性分析[J]. 中国科技
	信息, 2021(9): 86-88.
[5]	冯磊. 基于不同电离层模型的精密单点定位精度分析[J]. 测绘与
	空间地理信息, 2021, 44(1): 134-140.
[6]	李启航, 王剑, 刘瑞华. 45°(N)纬度带的 Klobuchar-like 电离层延迟
	季节修正模型与评估[J]. 中国空间科学技术, 2019, 39(6): 30-37.
[7]	章红平. 基于地基 GPS 的中国区域电离层监测与延迟改正研究[D].
	上海: 中国科学院研究生院(上海天文台), 2006.
	[8]
	RATNAM D V, DABBAKUTI J R K K, LAKSHMI N V V N J S． Improvement of Indian-regional klobuchar ionospheric model parameters for
	single-frequency GNSS users[J]． IEEE Geoscience and Remote Sensing
	Letters, 2018, 15(7): 971-975．
	[9]
	JONGSINTA WEE S, RUNRAENGWAJIAKE S, SUPNITHI P, et al．
	Improvement of GPS positioning accuracy when utilizing Klobuchar
	model with ionospheric conditions in Thailand[C]//2016 13th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), June 28-
	July 1, 2016, Chiang Mai, Thailand． IEEE, 2016: 1-5．
[10]	TONGKASEM N， SUPNITHI P, PHAKPHISUT W, et al. Improvement
	of GPS positioning accuracy when utilizing Klobuchar model with iono－
	spheric conditions in Thailand [C]//2019 34th International Technical
	Conference on Circuits/Systems, Computers and Communications (ITCCSCC), June, JeJu, Korea (South). IEEE, 2019: 1-4.
[11]	NISHIMOTO K, OHASHI M, KUBO Y, et al． Determination of the parameters of a Japanese-regional klobuchar ionospheric model based on
	GR models and SCH analysis by GEONET data[C]//ION Pacific PNT
	Meeting, Honolulu, Hawaii, 2013: 723-734.
[12]	王文中, 张树生, 余隋怀. 基于粒子群优化的 BP 神经网络图像复原
	算法研究[J]. 西北工业大学学报, 2018, 36(4): 709-714.
[13]	ICAO. 航空电信: 第一卷无线电助航设施(第七版): Annex 10[S]. Montreal: ICAO, 2018.
[14]	李作虎. 卫星导航系统性能监测及评估方法研究[D]. 郑州: 解放军
	信息工程大学, 2012.