| 联合高度角与信噪比的精化随机模型及其对高纬度精密单点定位的影响 |
| |
| 引用本文： | 吕明慧,李薇,张宝成,柴艳菊.联合高度角与信噪比的精化随机模型及其对高纬度精密单点定位的影响[J].全球定位系统,2021,46(3):15. |
| |
| 作者姓名： | 吕明慧 李薇 张宝成 柴艳菊 |
| |
| 作者单位： | 1.中国科学院精密测量科学与技术创新研究院，武汉 430071 |
| |
| 摘 要： | 利用主成分分析法(PCA)确定了观测噪声中高度角和信噪比(SNR)的贡献，在此基础上建立了精化的全球卫星导航系统(GNSS)随机模型，并验证了基于此随机模型的高纬度测站精密单点定位(PPP)效果. 结果表明:在高纬度地区精化随机模型相比于仅顾及高度角或SNR的传统随机模型效果更佳，定位精度较高度角模型提高约30%，较SNR模型提高约20%. 在高程方向上精度提高最为明显，对比高度角模型和SNR模型分别提高约37%和24%. 该研究对提高高纬度地区GNSS定位精度有一定的参考价值.
|
| 关 键 词： | 全球卫星导航系统(GNSS) 精密单点定位(PPP) 随机模型 主成分分析法(PCA) 高纬度 |
| 收稿时间： | 2020-12-21 |
Refined stochastic model of combining elevation angle and SNR and its impact on precise point positioning in high latitude areas |
| |
| Institution: | 1.Innovation Academy for Precision Measurement Science and Technology, CAS, Wuhan 430071, China2.University of Chinese Academy of Sciences, Beijing 100049, China |
| |
| Abstract: | Principal component analysis method is used to determine the contribution of elevation angle and signal to noise ratio (SNR) in observation noise, and a refined Global Navigation Satellite System (GNSS) stochastic model is established based on the analysis results. The performance of the refined stochastic model is verified by using precision point positioning (PPP). It shows that the refined stochastic model leads to better positioning results in high latitude areas than traditional model that only takes into account elevation angle or SNR. The refined stochastic model is about 30% more accurate than elevation angle model, and about 20% better than SNR model. The accuracy of refined stochastic model improves most obvious in the zenith direction, and the improvements are about 38% and 24% with respect to the results of elevation angle model and SNR model, respectively. This study indicates that our new refined stochastic model is advantage to high-precision positioning accuracy in high latitude areas. |
| |
| Keywords: | |
|
| 点击此处可从《全球定位系统》浏览原始摘要信息 |
| 点击此处可从《全球定位系统》下载免费的PDF全文 |
