The location service is an important part of the smart city. A unified location service for outdoor and indoor/overground and underground activity will assist the construction of smart cities. However, with different coordinate systems and data formats, it is difficult to unify various positioning technologies on the same basis. Global navigation satellite system (GNSS)-based positioning is the only way to provide absolute location under the Earth-centered, Earth-fixed coordinate system (ECEF). Increasing indoor and underground human activity places significant demand on location-based services but no GNSS signals are available there. Fortunately, a type of satellite that is indoors, known as pseudolite, can transmit GNSS-like ranging signals. Users can obtain their position by receiving ranging signals and their resection without adding or switching other sensors when they go from outdoors to indoors. To complete the outreach of the GNSS indoors and underground to support the smart city, how to adapt the pseudolite design and unify coordinate frames for linking to the GNSS remain to be determined. In this regard, we provide an overview of the history of the research and application of pseudolites, the research progress from both the system side and the user side, and the plans for pseudolite-based location services in smart cities.

At 21:48 on 21 May 2021, an Ms 6.4 earthquake occurred in Yangbi County, Dali Prefecture, Yunnan Province. At present, uncertainty remains regarding the source parameters and deformation mechanism of the Yangbi earthquake. In this study, we determine fault geometry and slip distribution of the earthquake by InSAR analysis. Then, the Coulomb stress loading caused by the Yangbi earthquake is further analyzed. The results show that the moment magnitude of the Yangbi earthquake was Mw 6.14. The slip mainly occurred at depths of 3–13 km, with a maximum slip of approximately 61 cm at a depth of 6.98 km. The Yangbi earthquake was triggered by a blind fault in the NW-SE in the west parallel to the Weixi-Weishan Fault and its seismogenic fault exhibits strike-slip displacement. A large number of aftershocks were distributed along the fault rupture surface where the Coulomb stress increases. As the depth of the crust increases, the area where the Coulomb stress increases in the Yangbi earthquake, decreases. The occurrence of this earthquake also caused a significant increase in the Coulomb stress in the southeastern section of the Weixi-Weishan Faul. We should pay more attention to its seismic hazards.

Real-time kinematic (RTK) is a technique frequently utilized to provide real-time highly precise positioning services for mobile Internet-of-Things (IoT)-embedded terminals from intelligence appliances and smartphones to autonomous drones and self-driving vehicles. To fully utilize hardware resources, the internal GNSS chips or modules equipped in IoT terminals should satisfy the traits of energy efficiency and low computational complexity. As the number of global navigation satellite system (GNSS) increases, the continuous accumulation of high-dimensional rounding errors, the rough system model, and seriously distorted observations will result in divergence and considerable processing burden in the conventional Kalman filter (KF) process. Computational efficiency is significant in the reduction in the power consumption and intensifies the positioning performance of GNSS receivers. Here, a new filter strategy based on UD factorization, where U stands for the unit upper-triangular factor and D indicates the diagonal factor, is proposed for RTK positioning to enhance the numerical stability and reduce the computational effort. The equivalent principle was applied to turn double-difference (DD) observations into zero-difference (ZD) observations. Then, the UD-factorization-based Kalman filter (UD-KF) is proposed as a way to sequentially provide accurate real-time estimations of the filter states and variance–covariance (VC) matrix. Both static and dynamic tests were carried out with single-frequency data from a GPS to evaluate the performance of UD-KF. The results of the zero-baseline test show that UD-KF can obtain smaller RMS of the estimated parameters as the noise of DD observations was twice that of the ZD observations. A short baseline test showed that, compared to the regular filter approach with DD observations, UD-KF achieved a shorter computation time with a higher data utilization rate for both filtering and fixing stages, with an average improvement of 32% and 18%. Finally, a dynamic test showed that the UD-KF can avoid the undesirable effect of satellite changes. Therefore, compared to KF with DD observations, the UD-KF with equivalent ZD observations can enhance the robustness as well as improve the positioning accuracy of RTK positioning.