# Experimental Study of Accuracy of High-Rate GNSS in Context of Structural Health Monitoring
## 1 Introduction  
Civil engineering structures, such as long-span bridges and tall buildings, are critical components of urban infrastructures. The conditions of these engineering structures are normally monitored closely as they may deteriorate over time, and the loadings may also change due to, e.g., increasing traffic loads on a bridge [1, 2]. The failure of an engineering structure may disrupt transport and lead to casualties and economic losses [3]. Global Navigation Satellite Systems (GNSS)-based technologies have been widely used in monitoring displacements of engineering structures and ground motions (e.g., [4, 5]). GNSS-based technologies have a distinct advantage in that they are able to provide accurate real-time displacement information. Two main GNSS data processing strategies have been in use in structural health monitoring: real-time kinematic (RTK) positioning and precise point positioning (PPP) [6]. Most of the GNSS positioning errors (e.g., clock errors, orbit errors, and tropospheric and ionospheric effects) can be removed in RTK positioning, resulting inup to millimeter-level displacement accuracy [7]. The RTK positioning technique has been widely used for monitoring engineering structures, including high-rise buildings, bridges, dams, and wind turbines [8; 9; 10; 11]. The accuracy of RTK positioning decreases in general with the length of the baseline [12]. The PPP positioning technique obtains positioning information with a standalone GNSS receiver [13]. Aided with a precise ephemeris, the positioning accuracy of PPP can be up to the centimeter level [14; 15]. The technique of PPP with ambiguity resolution (PPP-AR) can further enhance positioning accuracy [16]. PPP and PPP-AR techniques have also been applied in applications such as seismic waveform detection [17]. PPP and PPP-AR have been verified with a low-rate GNSS receiver, a shaking table, and field experiments for monitoring structural displacements [18]. Low data sampling rate GNSS receivers, typically 1-20 Hz, are the mainstream GNSS equipment deployed to date partly due to the wide availability of such GNSS equipment on the market. For example, [PERSON] et al. [19] monitored a bridge using a 1 Hz GPS/GLONASS RTK system to identify the bridge's dynamic characteristics. [PERSON] et al. [20] evaluated the performance of 10 Hz PPP with the help of a shaking table. Many 10-Hz GNSS RTK systems have been deployed on several real-world long-span bridges, e.g., the Severn suspension bridge in the UK, the Tsing Ma suspension bridge, and the Stonecutters cable-stayed bridge in Hong Kong [21]. However, it is often more desirable to have higher sampling rate data to better define the dynamic characteristics of engineering structures, which may be more suitable for monitoring structures with very high-frequency vibrations, such as the short-span railway bridge, or the bridge with earthquake loading. For example, [PERSON] et al. [22] reported that about one-quarter of the railway bridges in Switzerland exhibited natural frequencies above 10 Hz, with some of them reaching about 50 Hz, which is hard to detect based on the GNSS with a normal sampling rate. According to the Nyquist theorem, the Nyquist frequency of GNSS observations should be generally higher than the natural vibration frequency of the structures to avoid aliasing problems. [PERSON] et al. [23] indicated that displacement information from very high-rate GNSS was useful for monitoring structural health conditions. Moreover, with the advance in GNSS hardware technologies, the high-sampling rate GNSS receivers (typically 20-100 Hz) have become widely available and emerged as a promising technique for monitoring structural deformation and health assessment. For example, [PERSON] et al. [24] collected 50 Hz GPS data by a JAVAD TRIMMPH-1 receiver to monitor the displacement of a two-floor flexible steel frame model in real-time. [PERSON] and [PERSON] [25] used 100 Hz GNSS data (Javad Delta receiver) to study a stiff pedestrian bridge and then analyze the displacement noise characteristics [26].