高度角与信噪比混合的GNSS随机模型精化及其对RTK定位性能的影响

Refinement of GNSS stochastic model combining elevation angle and SNR and its effect on RTK positioning performance

  • 摘要: 全球卫星导航系统(GNSS)观测值精度会受到大气延迟、非视距(NLOS)信号和多径等因素的影响,而高度角或信噪比(SNR)模型对不同误差源的敏感程度不一样,导致传统基于高度角或SNR的单一随机模型不能满足全场景的高精度定位导航,加上多频多系统的出现,不同GNSS甚至同一系统的不同频段观测值精度也会存在差异,这也给传统模型定权带来了一定挑战. 在分析高度角随机模型、SNR随机模型存在的优缺点的基础上,提出了一种高度角、SNR混合的随机模型;通过站间单差、历元间三次差分别对GPS、北斗卫星导航系统(BDS)、Galileo的伪距、相位噪声进行提取,精化了高度角、SNR混合随机模型. 实验表明,SNR模型、高度角模型、混合模型的模糊度正确固定率分别为92.42%、95.85%、97.69%;SNR模型定位精度低于高度角和混合模型,混合模型相比于高度角模型,水平方向上定位精度提升了50.0%,高程方向精度提升了37.1%.

     

    Abstract: The accuracy of Global Satellite System Navigation (GNSS) observations will be affected by atmospheric delay, NLOS signal, multipath and other factors. However, the sensitivity of elevation angle or SNR model to different error sources is different. As a result, the traditional single random model based on elevation angle or signal noise ratio (SNR) cannot meet the high-precision positioning and navigation of the whole scene, coupled with the emergence of multi frequency and multi system, the accuracy of observations in different frequency bands of different GNSS systems and even the same system will also be different, which also brings a great challenge to the traditional model weighting. Based on the analysis of the advantages and disadvantages of elevation random model and SNR random model, a combined random model of elevation angle and SNR is proposed in this paper; The pseudo-range and phase noise of GPS, BDS, Galileo are extracted respectively through single difference between stations and cubic difference between epochs, and the combined random model of extracted and SNR is refined. Experiments show that the correct fixing rates of ambiguity of SNR model, elevation angle model and combined model are 92.42%, 95.85% and 97.69% respectively; Compared with the elevation angle model, the positioning accuracy of the combined model is improved by 50.0% in the horizontal direction and 37.1% in the elevation direction.

     

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