Positioning using the Global Positioning System (GPS) is unreliable in dense urban areas with tall buildings and/or narrow streets, known as 'urban canyons'. This is because the buildings block, reflect or diffract the signals from many of the satellites. This paper investigates the use of 3-Dimensional (3-D) building models to predict satellite visibility. To predict Global Navigation Satellite System (GNSS) performance using 3-D building models, a simulation has been developed. A few optimized methods to improve the efficiency of the simulation for real-time purposes were implemented. Diffraction effects of satellite signals were considered to improve accuracy. The simulation is validated using real-world GPS and GLObal NAvigation Satellite System (GLONASS) observations. The performance of current and future GNSS in urban canyons is then assessed by simulation using an architectural city model of London with decimetre-level accuracy. GNSS availability, integrity and precision is evaluated over pedestrian and vehicle routes within city canyons using different combinations of GNSS constellations. The results show that using GPS and GLONASS together cannot guarantee 24-hour reliable positioning in urban canyons. However, with the addition of Galileo and Compass, currently under construction, reliable GNSS performance can be obtained at most, but not all, of the locations in the test scenarios. The modelling also demonstrates that GNSS availability is poorer for pedestrians than for vehicles and verifies that cross-street positioning errors are typically larger than along-street due to the geometrical constraints imposed by the buildings. For many applications, this modelling technique could also be used to predict the best route through a city at a given time, or the best time to perform GNSS positioning at a given location.

A low Earth orbiter (LEO)-based navigation signal augmentation system is considered as a complementary of current global navigation satellite systems (GNSS), which can accelerate precise positioning convergence, strengthen the signal power, and improve signal quality. Wuhan University is dedicated to LEO-based navigation signal augmentation research and launched one scientific experimental satellite named Luojia-1A. The satellite is capable of broadcasting dual-frequency band ranging signals over China. The initial performance of the Luojia-1A satellite navigation augmentation system is assessed in this study. The ground tests indicate that the phase noise of the oscillator is sufficiently low to support the intended applications. The field ranging tests achieve 2.6 m and 0.013 m ranging precision for the pseudorange and carrier phase measurements, respectively. The in-orbit test shows that the internal precision of the ephemeris is approximate 0.1 m and the clock stability is 3 × 10−10. The pseudorange and carrier phase measurement noise evaluated from the geometry-free combination is about 3.3 m and 1.8 cm. Overall, the Luojia-1A navigation augmentation system is capable of providing useable LEO navigation augmentation signals with the empirical user equivalent ranging error (UERE) no worse than 3.6 m, which can be integrated with existing GNSS to improve the real-time navigation performance.

In the past few decades, global navigation satellite system (GNSS) technology has been widely used in structural health monitoring (SHM), and the monitoring mode has evolved from long-term deformation monitoring to dynamic monitoring. This paper gives an overview of GNSS-based dynamic monitoring technologies for SHM. The review is classified into three parts, which include GNSS-based dynamic monitoring technologies for SHM, the improvement of GNSS-based dynamic monitoring technologies for SHM, as well as denoising and detrending algorithms. The significance and progress of Real-Time Kinematic (RTK), Precise Point Position (PPP), and direct displacement measurement techniques, as well as single-frequency technology for dynamic monitoring, are summarized, and the comparison of these technologies is given. The improvement of GNSS-based dynamic monitoring technologies for SHM is given from the perspective of multi-GNSS, a high-rate GNSS receiver, and the integration between the GNSS and accelerometer. In addition, the denoising and detrending algorithms for GNSS-based observations for SHM and corresponding applications are summarized. Challenges of low-cost and widely covered GNSS-based technologies for SHM are discussed, and problems are posed for future research.