A system level implementation of wavelet based filtering for GNSS signals

A project is presented to study the Global Positioning System and learn how to apply wavelet analysis to mitigate the effects of multipath errors on GNSS signals. The analysis is carried out using the SystemC language to demonstrate how one may try to implement the GPS signal wavelet filter in hardware. Wavelet analysis, the SystemC library and additional tools are discussed in detail. Design issues such as control signaling and position estimation are explained. System evaluation is performed at two levels, one using cross correlation of signals and the second by measuring the amount of clustering in position plots.

A system level implementation of wavelet based filtering for GNSS signals

A project is presented to study the Global Positioning System and learn how to apply wavelet analysis to mitigate the effects of multipath errors on GNSS signals. The analysis is carried out using the SystemC language to demonstrate how one may try to implement the GPS signal wavelet filter in hardware. Wavelet analysis, the SystemC library and additional tools are discussed in detail. Design issues such as control signaling and position estimation are explained. System evaluation is performed at two levels, one using cross correlation of signals and the second by measuring the amount of clustering in position plots.

GNSS Multipath Detection Using Continuous Time-Series C/N0

The reduction of multipath errors is a significant challenge in the Global Navigation Satellite System (GNSS), especially when receiving non-line-of-sight (NLOS) signals. However, selecting line-of-sight (LOS) satellites correctly is still a difficult task in dense urban areas, even with the latest GNSS receivers. This study demonstrates a new method of utilization of C/N0 of the GNSS to detect NLOS signals. The elevation-dependent threshold of the C/N0 setting may be effective in mitigating multipath errors. However, the C/N0 fluctuation affected by NLOS signals is quite large. If the C/N0 is over the threshold, the satellite is used for positioning even if it is still affected by the NLOS signal, which causes the positioning error to jump easily. To overcome this issue, we focused on the value of continuous time-series C/N0 for a certain period. If the C/N0 of the satellite was less than the determined threshold, the satellite was not used for positioning for a certain period, even if the C/N0 recovered over the threshold. Three static tests were conducted at challenging locations near high-rise buildings in Tokyo. The results proved that our method could substantially mitigate multipath errors in differential GNSS by appropriately removing the NLOS signals. Therefore, the performance of real-time kinematic GNSS was significantly improved.

A Low-Cost, High-Precision Vehicle Navigation System for Deep Urban Multipath Environment Using TDCP Measurements

In this study, we developed a low-cost, high-precision vehicle navigation system for deep urban multipath environments using time-differenced carrier phase (TDCP) measurements. Although many studies are being conducted to navigate autonomous vehicles using the global positioning system (GPS), it is difficult to obtain accurate navigation solutions due to multipath errors in urban environments. Low-cost GPS receivers that determine the solution based on pseudorange measurements are vulnerable to multipath errors. We used carrier phase measurements that are more robust for multipath errors. Without correction information from reference stations, the limited information of a low-cost, single-frequency receiver makes it difficult to quickly and accurately determine integer ambiguity of carrier phase measurements. We used TDCP measurements to eliminate the need to determine integer ambiguity that is time-invariant and we combined TDCP-based GPS with an inertial navigation system to overcome deep urban multipath environments. Furthermore, we considered a cycle slip algorithm for its accuracy and a multi-constellation navigation system for its availability. The results of dynamic field tests in a deep urban area indicated that it could achieve horizontal accuracy of at the submeter level.

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

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.

GNSS Array Antenna for Mitigating Multipath Errors in Urban Environment

GNSS signal vulnerability has been a major concern especially for safety-of-life applications such as aircraft operations. Therefore, a GNSS array antenna technology was investigated focusing on beamforming to mitigate multipath errors in urban environment including airport surfaces. A commercial three-element GNSS antenna and RF-Front end were used to obtain digital IF data. The recorded In-phase/Quadrature IF data for three antennas were combined with proper weight to form beams towards satellites after so-called hardware biases were calibrated. Test results in multipath-rich environment demonstrated that 50-70% reduction of pseudorange errors due to multipath were possible if the beamforming algorithms were applied.