Performance evaluation of a real-time high-precision landslide displacement detection algorithm based on GNSS virtual reference station technology

全球导航卫星系统应用 山崩 流离失所(心理学) 全站仪 计算机科学 遥感 实时计算 大地测量学 算法 全球定位系统 地质学 电信 地震学 心理学 心理治疗师
作者
Pengxu Wang,Hui Liu,Guigen Nie,Zhixin Yang,Jiaji Wu,Chuang Qian,Bao Shu
出处
期刊:Measurement [Elsevier BV]
卷期号:199: 111457-111457 被引量:25
标识
DOI:10.1016/j.measurement.2022.111457
摘要

Global navigation satellite system (GNSS) technology is one of the most effective landslide displacement monitoring methods, but most of the current landslide research based on GNSS is focused on long-term landslide monitoring, but short-term landslide monitoring is particularly important for the early warning of landslides. The main purpose of this paper is to extend the existing GNSS positioning model and design a set of different landslide displacement detection algorithms, which can guarantee high-precision displacement detection and give consideration to real-time, mainly for short-term landslide displacement, and can also give consideration to long-term landslide monitoring. In addition, the traditional layout mode of "one reference station corresponds to one landslide" has many problems, such as high cost, low utilization rate of reference station and excessive reliance on single reference station, which restrict the large-scale promotion and application of GNSS in landslide monitoring. Based on the existing VRS processing method and the displacement detection algorithm presented in this paper, the service effect of virtual reference station and physical reference station is compared and analyzed in detail, and the feasibility of virtual reference station replacing physical reference station is demonstrated. Experimental results show that the positioning accuracy of real time kinematic (RTK) is slightly worse than that of physical reference station due to the existence of atmospheric residual errors in the regional reference station network when VRS replaces physical reference station for displacement detection. However, after processing the real-time sliding window model, it significantly suppressed the influence of all kinds of observation noise and gross error, and the solution accuracy of the output sliding window period was not much different from that of the physical reference station, basically at the sub-centimeter level, which could fully meet the needs of centimeter and sub-centimeter level landslide displacement detection. In addition, the "short and long period mutual checking method" proposed in this paper can realize the detection and early warning of the rapid displacement type in a short period by reasonably adjusting the window length of the short and long period. The " epoch difference method" can realize the detection and early warning of the sudden displacement in a few epoch. In practical application, the combined detection of the two methods can satisfy the real-time detection and early warning of short-term landslide displacement. In addition, by storing the solution positions of each long period sliding window period, the periodic position comparison can be carried out to judge the displacement changes of the monitoring body, which is equivalent to the usual long-term landslide monitoring strategy.
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