Displacement monitoring performance of relative positioning and Precise Point Positioning (PPP) methods using simulation apparatus

Alçay, Salih; Öğütçü, Sermet; Kalaycı, İbrahim; Yiğit, Cemal Özer

doi:10.1016/j.asr.2018.11.003

Cited by 28 publications

(14 citation statements)

References 23 publications

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“…It is worth mentioning that the number of observations is an essential factor that affects the energy of wavelet decompositions and the accuracy of results. In the case of using event 1 data only, the significant wavelet nodes based on the calculation wavelet energy were (3,0) and (3,1), and this affected the accuracy of the GNSS results. The range of dynamic displacement is calculated and found to be 38.08 and 33.89 mm for the relative-and PPP-GNSS methods, respectively.…”

Section: Motions' Characteristicsmentioning

confidence: 99%

“…Recently, the relative and precise point positioning (PPP) GNSS techniques have been intensively developed and used in structural health monitoring and detection of crustal movement applications [1][2][3][4]. By using high-rate sampling, amplitudes and frequencies of strong movements can be accurately detected in the position and frequency domains.…”

Section: Introductionmentioning

confidence: 99%

“…Xu et al [3] also found that PPP is capable of detecting seismic displacement at the same level as the relative GNSS method. Furthermore, Alcay et al [1] compared PPP solutions with relative GNSS positioning considering different session lengths (24,12,8,4, and 2 h) for monitoring permanent (static) displacement in the horizontal and vertical directions. The study showed that 24 to 8 h observation durations for both methods have high consistency in detecting actual displacement in the horizontal direction.…”

Section: Introductionmentioning

confidence: 99%

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Hybrid Wavelet and Principal Component Analyses Approach for Extracting Dynamic Motion Characteristics from Displacement Series Derived from Multipath-Affected High-Rate GNSS Observations

et al. 2019

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Nowadays, the high rate GNSS (Global Navigation Satellite Systems) positioning methods are widely used as a complementary tool to other geotechnical sensors, such as accelerometers, seismometers, and inertial measurement units (IMU), to evaluate dynamic displacement responses of engineering structures. However, the most common problem in structural health monitoring (SHM) using GNSS is the presence of surrounding structures that cause multipath errors in GNSS observations. Skyscrapers and high-rise buildings in metropolitan cities are generally close to each other, and long-span bridges have towers, main cable, and suspender cables. Therefore, multipath error in GNSS observations, which is typically added to the measurement noise, is inevitable while monitoring such flexible engineering structures. Unlike other errors like atmospheric errors, which are mostly reduced or modeled out, multipath errors are the largest remaining unmanaged error sources. The high noise levels of high-rate GNSS solutions limit their structural monitoring application for detecting load-induced semi-static and dynamic displacements. This study investigates the estimation of accurate dynamic characteristics (frequency and amplitude) of structural or seismic motions derived from multipath-affected high-rate GNSS observations. To this end, a novel hybrid model using both wavelet-based multiscale principal component analysis (MSPCA) and wavelet transform (MSPCAW) is designed to extract the amplitude and frequency of both GNSS relative- and PPP- (Precise Point Positioning) derived displacement motions. To evaluate the method, a shaking table with a GNSS receiver attached to it, collecting 10 Hz data, was set up close to a building. The table was used to generate various amplitudes and frequencies of harmonic motions. In addition, 50-Hz linear variable differential transformer (LVDT) observations were collected to verify the MSMPCAW model by comparing their results. The results showed that the MSPCAW could be efficiently used to extract the dynamic characteristics of noisy dynamic movements under seismic loads. Furthermore, the dynamic behavior of seismic motions can be extracted accurately using GNSS-PPP, and its dominant frequency equals that extracted by LVDT and relative GNSS positioning method. Its accuracy in determining the amplitude approaches 91.5% relative to the LVDT observations.

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Section: Motions' Characteristicsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Hybrid Wavelet and Principal Component Analyses Approach for Extracting Dynamic Motion Characteristics from Displacement Series Derived from Multipath-Affected High-Rate GNSS Observations

et al. 2019

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“…Precise Point Positioning (PPP) and relative positioning techniques are commonly used for applications that require sub-centimeter levels of precision (Alcay et al 2019). Conventionally, precise orbit and clock products from one of the International GNSS Service (IGS) analysis centres are used to remove satellite orbit and clock errors (Kouba and H eroux 2001).…”

Section: Introductionmentioning

confidence: 99%

Simulation case study of displacement monitoring using network derived positioning

Öğütçü

2020

Geomatics, Natural Hazards and Risk

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Network-based real-time kinematic (NRTK) GNSS (Global NavigationSatellite System) is among the most commonly used surveying technique in many countries for various applications that requires a single GNSS receiver. The main principle of this system is to generate reliable error models that can mitigate dispersive (e.g. ionospheric delay) and non-dispersive (e.g. tropospheric delay and orbit bias) errors, which are the main sources of the degradation of positioning accuracy. In this study, the performance of NRTK positioning for deformation and landslide monitoring is investigated using a simulation apparatus. For this purpose, 20 simulated two-dimensional and vertical displacements are conducted within a two-month period in 2019. The 24-h NRTK data with 1-s sampling intervals are obtained using a CHC N72 GNSS reference receiver for each displacement. The 24-h NRTK data are mutually subdivided into 12-, 6-, 3-and 1-h non-overlapping sessions to investigate the effect of observation time on monitoring displacement performance. Two filtering methodsnamely, averaging the raw observations and averaging the observations derived from Kalman filteringare chosen for each session. The displacements obtained from the filtered NRTK observations are compared to the simulated (true) displacements. Another experiment is carried out to monitor the displacement in real time using first-order low-pass and moving-average filters. The NRTK data are collected during the displacement for a real-time experiment. The results of the experiments indicate that 1-sigma horizontal and vertical Root Mean Square errors (RMSEs) of displacements between the filtered NRTK data and true displacements are determined to be 1.5 and 5.4 mm, respectively, using 24-h data. The results also suggest that no significant difference is observed between the filtering methods for most of the points. The RMSE of the two-dimensional displacement direction between the azimuth angle derived from the filtered NRTK data and the azimuth angle of true direction is found to be 15 for 3 mm displacement using 24-h data. For detecting the displacements visually in real time, the minimum magnitude of displacements needs to be 7 mm and 10 mm for the horizontal and vertical components, respectively, to distinguish the displacements from the noise.

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“…In this method, position can be determined by using a single GNSS receiver. Many studies have been carried out on the performance of the Post Process PPP method [3,4,5,6,7,8]. With static and kinematic PPP, a position accuracy of cm-dm level can be achieved.…”

Section: Introductionmentioning

confidence: 99%

Comparison of RT-PPP and RT-PPP-AR Methods

Alçay¹,

Atiz²,

Öğütçü³

2020

acperpro

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The Precise Point Positioning (PPP) is an absolute positioning method which emerged as an alternative to the relative positioning method. This method is widely used in many applications in recent years. In this method the static and kinematic positioning can be performed with high accuracy by using single GNSS receiver. In the last few years, the PPP method has started to be used in real time (RT-PPP) thanks to the real-time precise products (satellite orbit and clock data) produced by different organizations like IGS, BKG, CNES, ESA, EUREF, GFZ etc. The high interest in RT-PPP has accelerated the development of this method and many software have been developed. Recently, some of the software have ability to apply integer ambiguity resolution (AR). For this purpose, in this study the positioning performance of RT-PPP method was tested using two options of PPP-WIZARD software (RT-PPP, RT-PPP-AR). Three IGS stations were chosen in different geographical regions. The real-time coordinates of the stations belong to the observation period of about 4 hours were derived simultaneously with the RT-PPP and RT-PPP-AR options in 1 second epoch interval. The results obtained are given in a comparative approach.

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Displacement monitoring performance of relative positioning and Precise Point Positioning (PPP) methods using simulation apparatus

Cited by 28 publications

References 23 publications

Hybrid Wavelet and Principal Component Analyses Approach for Extracting Dynamic Motion Characteristics from Displacement Series Derived from Multipath-Affected High-Rate GNSS Observations

Hybrid Wavelet and Principal Component Analyses Approach for Extracting Dynamic Motion Characteristics from Displacement Series Derived from Multipath-Affected High-Rate GNSS Observations

Simulation case study of displacement monitoring using network derived positioning

Comparison of RT-PPP and RT-PPP-AR Methods

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