A procedure for the significance testing of unmodeled errors in GNSS observations
文献类型：期刊论文
| 作者 | Li, Bofeng1,2; Yang, Ling1; Shen, Yunzhong1; Zhang, Zhetao1 |
| 刊名 | JOURNAL OF GEODESY
 |
| 出版日期 | 2018-10-01 |
| 卷号 | 92期号:10页码:1171-1186 |
| 关键词 | GNSS Unmodeled error Significance testing Nonstationary signal Stationary signal White noise |
| ISSN号 | 0949-7714 |
| DOI | 10.1007/s00190-018-1111-9 |
| 英文摘要 | It is a crucial task to establish a precise mathematical model for global navigation satellite system (GNSS) observations in precise positioning. Due to the spatiotemporal complexity of, and limited knowledge on, systematic errors in GNSS observations, some residual systematic errors would inevitably remain even after corrected with empirical model and parameterization. These residual systematic errors are referred to as unmodeled errors. However, most of the existing studies mainly focus on handling the systematic errors that can be properly modeled and then simply ignore the unmodeled errors that may actually exist. To further improve the accuracy and reliability of GNSS applications, such unmodeled errors must be handled especially when they are significant. Therefore, a very first question is how to statistically validate the significance of unmodeled errors. In this research, we will propose a procedure to examine the significance of these unmodeled errors by the combined use of the hypothesis tests. With this testing procedure, three components of unmodeled errors, i.e., the nonstationary signal, stationary signal and white noise, are identified. The procedure is tested by using simulated data and real BeiDou datasets with varying error sources. The results show that the unmodeled errors can be discriminated by our procedure with approximately 90% confidence. The efficiency of the proposed procedure is further reassured by applying the time-domain Allan variance analysis and frequency-domain fast Fourier transform. In summary, the spatiotemporally correlated unmodeled errors are commonly existent in GNSS observations and mainly governed by the residual atmospheric biases and multipath. Their patterns may also be impacted by the receiver. |
| 资助项目 | National Natural Science Foundation of China[41574023] ; National Natural Science Foundation of China[41622401] ; National Natural Science Foundation of China[41504022] ; Technology Innovation Action Plan of Shanghai Science and Technology Committee[17511109501] ; National Key Research and Development Program of China[2016YFB0501802] ; Fundamental Research Funds for the Central Universities |
| WOS研究方向 | Geochemistry & Geophysics ; Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:000443563100006 |
| 出版者 | SPRINGER |
| 源URL | [http://202.127.146.157/handle/2RYDP1HH/5654]  |
| 专题 | 中国科学院武汉植物园 |
| 通讯作者 | Li, Bofeng; Zhang, Zhetao |
| 作者单位 | 1.Tongji Univ, Coll Surveying & GeoInformat, Shanghai 200092, Peoples R China 2.Chinese Acad Sci, Inst Geodesy & Geophys, State Key Lab Geodesy & Earths Dynam, Wuhan, Hubei, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Bofeng,Yang, Ling,Shen, Yunzhong,et al. A procedure for the significance testing of unmodeled errors in GNSS observations[J]. JOURNAL OF GEODESY,2018,92(10):1171-1186. |
| APA | Li, Bofeng,Yang, Ling,Shen, Yunzhong,&Zhang, Zhetao.(2018).A procedure for the significance testing of unmodeled errors in GNSS observations.JOURNAL OF GEODESY,92(10),1171-1186. |
| MLA | Li, Bofeng,et al."A procedure for the significance testing of unmodeled errors in GNSS observations".JOURNAL OF GEODESY 92.10(2018):1171-1186. |
入库方式： OAI收割
来源：武汉植物园
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