The performance of Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) integrated navigation can be severely degraded in urban canyons due to the non-line-of-sight (NLOS) signals and multipath effects. Therefore, to achieve a high-precision and robust integrated system, real-time fault detection and localization algorithms are needed to ensure integrity. Currently, the residual chi-square test is used for fault detection in the positioning domain, but it has poor sensitivity when faults disappear. Three-dimensional (3D) light detection and ranging (LiDAR) has good positioning performance in complex environments. First, a LiDAR aided real-time fault detection algorithm is proposed. A test statistic is constructed by the mean deviation of the matched targets, and a dynamic threshold is constructed by a sliding window. Second, to solve the problem that measurement noise is estimated by prior modeling with a certain error, a LiDAR aided real-time measurement noise estimation based on adaptive filter localization algorithm is proposed according to the position deviations of matched targets. Finally, the integrity of the integrated system is assessed. The error bound of integrated positioning is innovatively verified with real test data. We conduct two experiments with a vehicle going through a viaduct and a floor hole, which, represent mid and deep urban canyons, respectively. The experimental results show that in terms of fault detection, the fault could be detected in mid urban canyons and the response time of fault disappearance is reduced by 70.24% in deep urban canyons. Thus, the poor sensitivity of the residual chi-square test for fault disappearance is improved. In terms of localization, the proposed algorithm is compared with the optimal fading factor adaptive filter (OFFAF) and the extended Kalman filter (EKF). The proposed algorithm is the most effective, and the Root Mean Square Error (RMSE) in the east and north is reduced by 12.98% and 35.1% in deep urban canyons. Regarding integrity assessment, the error bound can overbound the positioning errors in deep urban canyons relative to the EKF and the mean value of the error bounds is reduced.

Equatorial plasma bubbles (EPBs) can cause large total electron content (TEC) gradient magnitudes and significant density irregularities. In this paper, depletions and irregularities due to EPBs are identified by using the Global Positioning System (GPS)-TEC time series extracted from nine Global Navigation Satellite System (GNSS) stations over Hong Kong near the equatorial ionization anomaly (EIA) crest region from 2013 to 2019. The correlation analyses between the daily variation in the rate of TEC change index (ROTI) and that of the EPB occurrence rate, depth, and duration are presented. The monthly EPB occurrence rate, depth, duration, and ROTI show strong seasonal variations, with maxima during equinoctial seasons, especially during the moderate-to-high solar activity years of 2013–2016. Furthermore, two seasonal asymmetries can be clearly seen for these parameters from 2013 to 2016. The EPB occurrences rate, depth, and duration vary annually with the solar radio flux at 10.7 cm (F10.7) index. The correlation analyses of the EPB occurrence rate, depth, and duration are found to be much more strongly correlated with the F10.7 index on an annual basis than on a monthly basis. The correlation analysis of monthly variations shows the impacts of solar activity on EPB occurrence, depth, and duration are seasonally dependent, which is significantly greater in the equinoctial seasons and summer than in winter.

Electromagnetic forming (EMF) is a forming process that relies on the inductive electromagnetic force to deform metallic workpiece at high speed. Calculation of the electromagnetic force is essential to understand the EMF process. However, accurate calculation requires complex numerical solution, in which the coupling between the electromagnetic process and the deformation of workpiece needs be considered. In this paper, an appropriate formula has been developed to calculate the electromagnetic force in metal work-piece in the sheet EMF process. The effects of the geometric size of coil, the material properties, and the parameters of discharge circuit on electromagnetic force are taken into consideration. Through the formula, the electromagnetic force at different time and in different positions of the workpiece can be predicted. The calculated electromagnetic force and magnetic field are in good agreement with the numerical and experimental results. The accurate prediction of the electromagnetic force provides an insight into the physical process of the EMF and a powerful tool to design optimum EMF systems.

Considering the inertial measurement unit (IMU) faults risk of an unmanned aerial vehicle (UAV), this paper provides an analysis of the error overboundings of position estimation in a tightly coupled IMU/global navigation satellite system (GNSS) integrated architecture under the IMU fault conditions using an error-state EKF-based approach and provides a comparison to a recently published EKF-based full state method. Simulation results show that both the error overboundings of the error-state and full-state EKFs can fit the state error against the IMU faults, but the error-state EKF is more suitable for UAV navigation system integrity assurance due to its higher calculation eciency. This study will be extended to the integrity monitoring of multisensor systems.