基于多源数据的BKlob模型精细化

刘家龙; 朱永兴; 贾小林; 宋淑丽; 程娜

doi:10.12265/j.gnss.2023092

基于多源数据的BKlob模型精细化

doi: 10.12265/j.gnss.2023092

刘家龙^{1, 2,},
朱永兴^{3, 4,},
贾小林^{3, 4,},
宋淑丽^{1, 2, ,},
程娜^5,

1.
中国科学院上海天文台, 上海 200030
2.
中国科学院大学, 北京 100080
3.
西安测绘研究所, 西安 710054
4.
地理信息工程国家重点实验室, 西安 710054
5.
山东建筑大学测绘地理信息学院, 济南 250101

基金项目: 国家自然科学基金(12073063)；地理信息工程国家重点实验室基金(SKLGIE2020-M-1-1)；山东省自然科学基金(ZR2021QD080)

详细信息

作者简介:
刘家龙：(1997—)，男，博士，研究方向为GNSS数据处理及电离层监测

通信作者:
宋淑丽 E-mail: slsong@shao.ac.cn

中图分类号: P288
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- 被引次数: 0
出版历程
- 收稿日期: 2023-04-18

Refinement of BKlob model based on multi-source data

LIU Jialong^{1, 2
,},
ZHU Yongxing^{3, 4
,},
JIA Xiaolin^{3, 4
,},
SONG Shuli^{1, 2
, ,},
CHENG Na^5
,

1.
Shanghai Observatory, Chinese Academy of Sciences, Shanghai 200030, China
2.
University of Chinese Academy of Sciences, Beijing 100080, China
3.
Xi’an Institute of Surveying and Mapping, Xi’an 710054, China
4.
State Key Laboratory of Geographic Information Engineering, Xi’an 710054, China
5.
School of Surveying and Geo-infomatics, Shandong Jianzhu University, Ji’nan 250101, China

摘要

摘要: 北斗三号全球卫星导航系统(BDS-3)开通了全球服务，BDS Klobuchar(BDSklob)模型的服务区域也拓展至全球范围，BDSklob模型全球化后的性能引起了极大的关注. 针对北斗二号卫星导航系统(BDS-2)播发的BDSklob模型在服务区域外精度不高、两极地区改正异常情况，本文基于参数精化方法，利用经验模型IRI-Plas-2017、北斗全球广播电离层延迟修正模型(BDGIM)，以及欧洲定轨中心(CODE)的全球电离层格网(GIM)产品多源数据提出新的BDSklob模型精细化方案多源数据精细化法. 结果表明：各个数据源精细化方法对BDSklob模型性能都有明显提升，尤其是在极地区域；BDSklob_C(数据源为CODE的GIM产品)处理结果精度最高；BDSklob_B(数据源为BDGIM)精度次之，但不借助外部数据源，在北斗系统中即可完成精化处理；BDSklob_I(数据源为IRI模型)精度稍差，但基于经验模型的预测性，可以满足实时精化处理的需要.
- BDS Klobuchar 模型 /
- 精细化 /
- 全球参考电离层模型(IRI模型) /
- 全球电离层格网(GIM) /
- 广播电离层模型
Abstract: BDS-3 has launched global services, and the service area of the BDS Klobuchar (BDSklob) model has also expanded to a global scale. The global performance of the BDSklob model has also attracted great attention. In response to the low accuracy of the BDSklob model outside the service area and abnormal correction in polar regions during the BDS-2 period, this paper proposes a new BDSklob model refinement scheme-multi-source data refinement method-based on parameter refinement method, using empirical models IRI-Plas-2017, BDGIM model, and multi-source data from CODE’s GIM products. The results show that the refinement methods of various data sources have significantly improved the performance of the BDSklob model, especially in polar regions; BDSklob_ C (GIM product with CODE data source) has the highest processing accuracy; BDSklob_ B (data source is BDGIM) takes the second place in accuracy, but without the help of external data sources, refinement processing can be completed in the Beidou system; BDSklob_ the accuracy of I (data source is IRI model) is slightly poor, but based on the predictive ability of empirical models, it can meet the needs of real-time refinement processing.
- BDS Klobuchar model /
- refinement /
- IRI model /
- GIM /
- broadcast ionospheric model

HTML全文

图 1 GNSS观测站分布图

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图 2 多源数据精化前后BDSklob模型与CODG TEC偏差

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图 3 精化前后BDSklob模型在不同区域上的改正率

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图 4 精化前后BDSklob模型在不同区域上的RMS

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图 5 2019年DOY172多源数据精化前后BDSklob模型与GNSS实测TEC偏差

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图 6 以GNSS实测TEC为基准精化前后BDSklob模型在不同区域上的RMS

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图 7 2019年两分两至日XIA1测站定位精度

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图 8 XIA1测站定位误差序列图

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表 1 精化前后BDSklob模型全球及区域精度统计

季节	模型	全球		亚太地区
季节	模型	PER/%	RMS/TECU	PER/%	RMS/TECU
春分	BDSklob	26.77	64.90	37.40	15.11
	BDSklob_B	39.14	7.03	45.31	6.96
	BDSklob_C	42.89	5.01	49.76	5.14
	BDSklob_I	33.63	14.22	37.96	18.65
夏至	BDSklobb	22.30	12.34	33.61	6.87
	BDSklob_B	39.08	5.26	46.68	4.60
	BDSklob_C	39.09	5.11	45.85	4.64
	BDSklob_I	31.51	7.01	36.33	7.84
秋分	BDSklobb	24.09	68.67	33.88	12.37
	BDSklob_B	38.02	5.12	48.59	4.72
	BDSklob_C	39.74	4.71	50.78	4.39
	BDSklob_I	31.29	11.28	39.26	15.51
冬至	BDSklobb	38.21	53.32	45.86	9.30
	BDSklob_B	46.42	6.79	49.01	5.04
	BDSklob_C	48.82	4.97	50.77	4.41
	BDSklob_I	37.70	10.54	35.84	8.84

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