Critical government and industry sectors (such as law enforcement, transportation, communication, and finance) are growing increasingly dependent on Global Navigation Satellite Systems (GNSS) for positioning, navigation, and timing. At the same time, the availability of low-cost GNSS jamming devices are presenting a serious threat to GNSS and increasing the likelihood of outages to infrastructures relying on GNSS. The attacks range from malicious parties intentionally jamming GNSS signals within a targeted geographical region to uninformed users causing accidental interference. This paper is an overview of different approaches adopted to date to mitigate GNSS disruption caused by intentional and unintentional jamming. The first approach outlined in this paper is the use of inertial systems to aid GNSS. The second and third approaches are the filtering of jamming/interference in the spatial and time-frequency domains, respectively. The fourth approach is vector tracking of GNSS signals in the receiver.

Sensors play important roles for autonomous driving. Localization is definitely a key one. Undoubtedly, global positioning system (GPS) sensor will provide absolute localization for almost all the future land vehicles. In terms of driverless car, 1.5 m of positioning accuracy is the minimum requirement, since the vehicle has to keep in a driving lane that usually wider than 3 m. However, the skyscrapers in highly-urbanized cities, such as Tokyo and Hong Kong, dramatically deteriorate GPS localization performance, leading more than 50 m of error. GPS signals are reflected at modern glassy buildings, which caused the notorious multipath effect. Fortunately, the number of navigation satellite is rapidly increasing in a global scale, since the rise of multi-global navigation satellite system. It provides an excellent opportunity for positioning algorithm developer of GPS sensor. More satellites in the sky imply more measurements to be received. Novelty, this paper proposes to take advantage of the fact that clean measurements (refers to line-of-sight measurement) are consistent and multipath measurements are inconsistent. Based on this consistency check, the faulty measurements can be detected and excluded to obtain better localization accuracy. Experimental results indicate that the proposed method can achieve less than 1-m lateral positioning error in middle urban canyons.

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.

Reliable continuing positioning is a critical requirement for intelligent transportation systems (ITS). An integrated positioning system is presented, where the global navigation satellite systems (GNSS) real‐time kinematic (RTK) method was mainly used. When RTK is not available, positioning was maintained by using Doppler measurements or by low‐cost inertial measurement unit (IMU) coupled with vehicle odometer measurements. A new integrity monitoring (IM) method is presented that addresses each positioning mode of the proposed integrated system. Models for the protection levels (PLs) are presented to bound the position error (PE) along the direction of motion of the vehicle and for the cross‐track direction. Both direction components are needed, for instance for collision avoidance and for lane identification. The method was assessed through a kinematic test performed in a dense urban environment. Results showed that by integrating GNSS RTK, Doppler with IMU + odometer, positioning was available all the time. For RTK, positioning accuracy was less than a decimetre and the IM availability was 99%, where the PLs bounded the PEs and were less than an alert limit of 1 m. Positioning using Doppler and IMU + odometer measurements bridged RTK breaks but at the sub‐meter level accuracy when used for short periods.