Wavelet packets based denoising method for measurement domain repeat-time multipath filtering in GPS static high-precision positioning

Lau, Lawrence

doi:10.1007/s10291-016-0533-1

Cited by 62 publications

(42 citation statements)

References 22 publications

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“…The wavelet packet (WP) is a popularization of the traditional wavelet, which can divide the frequency domain adaptively [26]. There has been much research performed on structural vibration response analysis based on the WP technique [27][28][29][30]. Typically, the structural vibration response signal is mixed in with a lot of noise and WP is an efficient way to deal with the white noise.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Parameter Identification of a Long-Span Arch Bridge Based on GNSS-RTK Combined with CEEMDAN-WP Analysis

Xiong

Niu

2019

Applied Sciences

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Under the action of wind, traffic, and other influences, long-span bridges are prone to large deformation, resulting in instability and even destruction. To investigate the dynamic characteristics of a long-span concrete-filled steel tubular arch bridge, we chose a global navigation satellite systems-real-time kinematic (GNSS-RTK) to monitor its vibration responses under ambient excitation. A novel approach, the use of complete ensemble empirical mode decomposition with adaptive noise combined with wavelet packet (CEEMDAN-WP) is proposed in this study to increase the accuracy of the signal collected by GNSS-RTK. Fast Fourier transform (FFT) and random decrement technique (RDT) were adopted to calculate structural modal parameters. To verify the combined denoising and modal parameter identification methods proposed in this paper, we established the structural finite element model (FEM) for comparison. Through simulation and comparison, we were able to draw the following conclusions. (1) GNSS-RTK can be used to monitor the dynamic response of long-span bridges under ambient excitation; (2) the CEEMDAN-WP is an efficient method used for the noise reduction of GNSS-RTK signals; (3) after signal filtering and noise reduction, structural modal parameters are successfully derived through RDT and illustrated graphically; and (4) the first-order natural frequency identified by field measurement is slightly higher than the FEM in this work, which may have been caused by bridge damage or the inadequate accuracy of the finite element model.

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Section: Introductionmentioning

confidence: 99%

Dynamic Parameter Identification of a Long-Span Arch Bridge Based on GNSS-RTK Combined with CEEMDAN-WP Analysis

Xiong

Niu

2019

Applied Sciences

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“…Wavelet transform is a powerful tool used to smooth GNSS derived-displacement components [40]. Lau [41], Mosavi et al [42], and Yu et al [43] utilized wavelet transform to extract the semi-static and dynamic components of GNSS measurements. The main advantage of wavelet transform is its ability to separate the signals based on frequency bands, which allows the extraction of the smoothed signal using these bands and by reconstruction of the signal [37].…”

Section: Methodsmentioning

confidence: 99%

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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“…Owing to the unique condition of repeatable satellite geometry in about one sidereal day at continuous static antennas, the same multipath errors repeat at the same sidereal time of the next day [13] and so as the CNR if there are no abnormal ionospheric and tropospheric activities such as ionospheric scintillation. The method of calculating sidereal days used in this paper can be found in [23].…”

Section: Methodology Of Investigation and Experimental Data Descrimentioning

confidence: 99%

“…In GNSS, it is well known that refraction occurs when GNSS signals propagate in the ionosphere and troposphere, and reflection occurs when there is multipath [12,13]. …”

Section: Physics Of Atmospheric Refraction In Gnssmentioning

confidence: 99%

Investigation into the Effect of Atmospheric Particulate Matter (PM2.5 and PM10) Concentrations on GPS Signals

Lau

2017

Sensors

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The Global Positioning System (GPS) has been widely used in navigation, surveying, geophysical and geodynamic studies, machine guidance, etc. High-precision GPS applications such as geodetic surveying need millimeter and centimeter level accuracy. Since GPS signals are affected by atmospheric effects, methods of correcting or eliminating ionospheric and tropospheric bias are needed in GPS data processing. Relative positioning can be used to mitigate the atmospheric effect, but its efficiency depends on the baseline lengths. Air pollution is a serious problem globally, especially in developing countries that causes health problems to humans and damage to the ecosystem. Respirable suspended particles are coarse particles with a diameter of 10 micrometers or less, also known as PM10. Moreover, fine particles with a diameter of 2.5 micrometers or less are known as PM2.5. GPS signals travel through the atmosphere before arriving at receivers on the Earth’s surface, and the research question posed in this paper is: are GPS signals affected by the increased concentration of the PM2.5/PM10 particles? There is no standard model of the effect of PM2.5/PM10 particles on GPS signals in GPS data processing, although an approximate generic model of non-gaseous atmospheric constituents (<1 mm) can be found in the literature. This paper investigates the effect of the concentration of PM2.5/PM10 particles on GPS signals and validates the aforementioned approximate model with a carrier-to-noise ratio (CNR)-based empirical method. Both the approximate model and the empirical results show that the atmospheric PM2.5/PM10 particles and their concentrations have a negligible effect on GPS signals and the effect is comparable with the noise level of GPS measurements.

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Wavelet packets based denoising method for measurement domain repeat-time multipath filtering in GPS static high-precision positioning

Cited by 62 publications

References 22 publications

Dynamic Parameter Identification of a Long-Span Arch Bridge Based on GNSS-RTK Combined with CEEMDAN-WP Analysis

Dynamic Parameter Identification of a Long-Span Arch Bridge Based on GNSS-RTK Combined with CEEMDAN-WP Analysis

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

Investigation into the Effect of Atmospheric Particulate Matter (PM2.5 and PM10) Concentrations on GPS Signals

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