高纬度地区PPP接收机跟踪噪声随机模型拟合改进

doi:10.11947/j.AGCS.2024.20230323

测绘学报 ›› 2024, Vol. 53 ›› Issue (4): 666-676.doi: 10.11947/j.AGCS.2024.20230323

高纬度地区PPP接收机跟踪噪声随机模型拟合改进

林英宗¹^,²^,³(), 罗小敏¹^,²(), 杜俊锋⁴

^1.中国地质大学（武汉）地质探测与评估教育部重点实验室，湖北　武汉　430074
^2.中国地质大学（武汉）地理与信息工程学院，湖北　武汉　430078
^3.武汉大学湖北珞珈实验室，湖北　武汉　430079
^4.武汉大学卫星导航定位技术研究中心，湖北　武汉　430079

收稿日期:2023-08-08 修回日期:2024-02-18 发布日期:2024-05-13
通讯作者: 罗小敏 E-mail:Linyzz@whu.edu.cn;luoxiaomin@cug.edu.cn
作者简介:林英宗（2000—），男，硕士生，研究方向为卫星导航定位。E-mail：Linyzz@whu.edu.cn
基金资助:
国家自然科学基金(42104029);中国博士后科学基金(2021M692975);湖北省博士后资助项目;地质探测与评估教育部重点实验室主任基金(GLAB2023ZR10);中央高校基本科研业务费

Fitting improvement of PPP receiver tracking error stochastic model for high latitudes

Yingzong LIN¹^,²^,³(), Xiaomin LUO¹^,²(), Junfeng DU⁴

^1.Key Laboratory of Geological Survey and Evaluation of Ministry of Education, China University of Geosciences (Wuhan), Wuhan 430074, China
^2.School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan 430078, China
^3.Hubei Luojia Laboratory, Wuhan University, Wuhan 430079, China
^4.GNSS Research Center, Wuhan University, Wuhan 430079, China

Received:2023-08-08 Revised:2024-02-18 Published:2024-05-13
Contact: Xiaomin LUO E-mail:Linyzz@whu.edu.cn;luoxiaomin@cug.edu.cn
About author:LIN Yingzong (2000—), male, postgraduate, majors in satellite navigation positioning. E-mail: Linyzz@whu.edu.cn
Supported by:
The National Natural Science Foundation of China(42104029);China Postdoctoral Science Foundation(2021M692975);Hubei Province Postdoctoral Foundation Project;The Opening Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education(GLAB2023ZR10);The Fundamental Research Funds for the Central Universities

摘要/Abstract

摘要：

电离层闪烁是指无线电信号的振幅和相位在短时间内出现快速随机波动的现象，可以导致全球导航卫星系统（GNSS）的测量噪声增大、信号丢失。目前，接收机跟踪误差随机模型（RTES）可以有效降低电离层闪烁对GNSS精密单点位定位（PPP）的影响。然而，该模型依赖专用型电离层闪烁监测接收机（ISMR）的数据产品。与遍布世界各地的测地型接收机相比，ISMR监测站的数量非常有限，并且获取ISMR数据产品也较为困难。本文利用加拿大高纬度北极电离层闪烁监测网络（CHAIN）2014—2022年的GPS观测数据与闪烁产品，提出了一种适用于高纬度地区测地型接收机的PPP随机模型，简称高纬接收机跟踪误差随机模型（HL_RTES）模型。HL_RTES模型采用振幅闪烁指数（S_4c）和总电子含量变化率指数（ROTI）来估计接收机跟踪噪声的方差，并通过对观测值进行重新加权以提高闪烁环境下PPP定位精度。利用2023年2月1日至2023年2月28日的CHAIN网跟踪站GPS数据进行单频仿动态PPP试验验证，结果表明，HL_RTES模型与RTES模型性能相当，都可以改进闪烁环境下PPP的定位精度；与高度角随机（EAS）模型相比，基于HL_RTES模型的PPP在水平、高程和3D方向的月平均RMS改善率分别为33.3%、42.8%和38.3%。此外，利用2023年2月15日IGS跟踪站INVK、KIRU、SCOR和URAL站数据进行试验验证发现，HL_RTES模型可以有效削弱高纬闪烁对PPP定位影响；相比于EAS模型，基于HL_RTES模型的4个站点PPP的3D RMS改善率分别为57.2%、32.9%、43.8%和31.4%。

关键词: 电离层闪烁, 精密单点定位, 随机模型, 测地型接收机

Abstract:

Ionospheric scintillation refers to the phenomenon of rapid random fluctuations in the amplitude and phase of radio signals which can result in increasing of measurement noise and signal loss of lock. At present, the receiver tracking error stochastic (RTES) model can effectively reduce the influence of ionospheric scintillation on GNSS precision point positioning (PPP). However, the RTES model relies on the data products from specialized ionospheric scintillation monitoring receivers (ISMR). Compared with geodetic receivers widely distributed around the world, the number of ISMR monitoring stations is very limited, and the acquisition of ISMR data products is difficult. Using the GPS observation and scintillation data recorded by the Canadian high arctic ionospheric network (CHAIN) during 2014—2022, this study proposes a PPP stochastic model suitable for geodetic GNSS receivers in high latitudes, referred to as the high latitude receiver tracking error (HL_RTES) model. The HL_RTES model uses S_4c index and rate of total electron content index (ROTI) to estimate the receiver tracking error variance, and the GPS positioning accuracy is improved by reweighting the observed values. The GPS observations of CHAIN station from February 1, 2023 to February 28, 2023 are used to conduct single-frequency mimics kinematic PPP experiment. Experimental results show that the performance of HL_RTES model and RTES model are comparable, and both can improve the PPP positioning accuracy under ionospheric scintillation; compared with EAS model, the monthly average RMS improvement rates of HL_RTES model in the horizontal, vertical and 3D directions are 33.3%, 42.8% and 38.3% respectively. In addition, using the data from the IGS stations INVK, KIRU, SCOR and URAL on February 15, 2023 to conduct experiment, it is found that the HL_RTES model can significantly mitigate the effects of high latitudes scintillation on PPP; compared with the EAS model, the improvement rates of HL_RTES model based PPP on the 3D RMS of the four stations are 57.2%, 32.9%, 43.8% and 31.4%, respectively.

Key words: ionospheric scintillation, PPP, stochastic model, geodetic receiver

中图分类号:

P228

林英宗, 罗小敏, 杜俊锋. 高纬度地区PPP接收机跟踪噪声随机模型拟合改进[J]. 测绘学报, 2024, 53(4): 666-676.

Yingzong LIN, Xiaomin LUO, Junfeng DU. Fitting improvement of PPP receiver tracking error stochastic model for high latitudes[J]. Acta Geodaetica et Cartographica Sinica, 2024, 53(4): 666-676.

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项目	策略
观测数据	L1频率的伪距和载波相位观测数据
采样间隔/s	30
截止高度角/(°)	10
精密卫星轨道	IGS精密产品星历
精密卫星钟差	IGS精密产品钟差
差分码偏差	CODE产品
相位缠绕	已经校正^[31]
天线相位中心偏移	igs14.atx
天线相位中心变化	igs14.atx
电离层延迟	作为参数进行估计
对流层延迟	使用Saastamoinen模型，其余部分作为随机游走进行估计
接收机坐标	作为白噪声进行估计和建模

测站	模型	RMS
测站	模型	东方向	北方向	高程方向	3D方向
ARCC	EAS	0.728	0.673	0.851	0.754
	RTES	0.255	0.344	0.509	0.384
	HL_RTES	0.253	0.453	0.767	0.535
CHUC	EAS	0.446	0.614	0.492	0.522
	RTES	0.144	0.379	0.236	0.271
	HL_RTES	0.304	0.387	0.260	0.321
DAWC	EAS	0.213	0.425	0.316	0.320
	RTES	0.307	0.398	0.286	0.334
	HL_RTES	0.146	0.316	0.245	0.246

高纬度地区PPP接收机跟踪噪声随机模型拟合改进

Fitting improvement of PPP receiver tracking error stochastic model for high latitudes

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