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Variance optimization of UWB observation based on map matching for PPP/INS/UWB tightly coupled positioning
Measurement Science and Technology ( IF 2.7 ) Pub Date : 2020-12-02 , DOI: 10.1088/1361-6501/abbf0c
Zengke Li 1, 2 , Long Zhao 1, 2 , Yifan Wang 1, 2 , Zhehua Yang 1, 2 , Zan Liu 1, 2 , Chengcheng Wang 1, 2
Affiliation  

Ultra-wideband (UWB) is essential in precise point positioning (PPP)/inertial navigation systems (INS)/UWB integrated navigation with the advantage of highly accurate observations. However, its accuracy could be affected by its sparse distribution, limited operating distance and low space height. In a dynamic environment, it is not easy to determine its variance precisely for an integrated system. Sometimes, the system performs poorly due to improper variance. In this paper, a map-matching variance optimization of UWB observation was firstly developed for tightly coupled positioning. Instead of the characteristic analysis of the UWB signal directly, the optimization can be realized based on the accuracy of PPP/INS solutions. The proposed map-matching algorithm can be adopted to access the accuracy of PPP/INS and determine the optimization factor so that the variance of UWB can be dynamically obtained. Then, the variance was adopted in the stochastic model of the PPP/INS/UWB system. The actual experiments were conducted to validate the proposed method under two different scenarios, and the effectiveness of this method was analysed. The results indicated that the proposed method could obtain suitable variance and improve the performance in both these two scenarios.



中文翻译:

基于地图匹配的PPP / INS / UWB紧密耦合定位的UWB观测方差优化

超宽带(UWB)在高精度点定位(PPP)/惯性导航系统(INS)/ UWB集成导航中至关重要,它具有高度精确的观测优势。但是,其精度可能会受到其稀疏分布,有限的工作距离和较小的空间高度的影响。在动态环境中,要为集成系统准确确定其方差并不容易。有时,由于不正确的方差,系统性能很差。在本文中,首先开发了一种UWB观测的地图匹配方差优化,用于紧密耦合定位。代替直接分析UWB信号的特性,可以基于PPP / INS解决方案的精度来实现优化。提出的地图匹配算法可以用来获得PPP / INS的精度并确定优化因子,从而可以动态获得UWB的方差。然后,在PPP / INS / UWB系统的随机模型中采用了方差。通过实际实验验证了该方法在两种情况下的有效性,并分析了该方法的有效性。结果表明,所提出的方法在这两种情况下都能获得合适的方差并提高性能。

更新日期:2020-12-02
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