Within the implementation of the European Geo-stationary Navigation Overlay System (EGNOS), a significant residual error in positioning is due to tropospheric delay effects. The EGNOS guidelines recommend that tropospheric delay is modelled using an empirical correction algorithm based on a receiver's height and estimates of meteorological parameters developed from average and seasonal variation data. However, such a simple average and seasonal variation model is unlikely to emulate temporal weather changes exactly. The potential errors involved in the application of the recommended algorithm and the consequent effects on the positioning errors, under typical UK weather conditions, are detailed in this paper. This was achieved by comparing tropospheric delays produced by the EGNOS model, with tropospheric delays estimated from high precision carrier phase GPS, over a one-year period for five UK stations. The RMS EGNOS model zenith tropospheric delay errors ranged from 4·0 to 4·7 cm, with maximum errors ranging from 13·2 to 17·8 cm. The errors were also shown to be spatially correlated. The subsequent effect on position error is shown to be dependent on the satellite elevation cut-off angle adopted and on whether or not the observations are weighted according to the satellite elevation angle.

Positioning, navigation, and timing (PNT) is essential for Internet of Things (IoT) communications and location-based services. Although global navigation satellite system (GNSS) can provide accurate PNT in open areas, obtaining reliable PNT is still a considerable technical challenge in complex urban environments. This is because the GNSS signals are more likely to be affected by multipath interference and nonline of sight (NLOS) reception issues arising from the obstructions and reflections in built environments. These introduce range measurement errors that degrade the GNSS positioning accuracy. This article proposes two resilient pseudorange error prediction and correction strategies to improve the GNSS positioning accuracy in urban environments. In particular, considering the carrier-to-noise density ( $C/N$ textsubscript 0), satellite elevation angle, and local positional information, the random forest-based pseudorange error prediction and correction models are constructed in two variations, including: 1) the point-based correction (PBC) and 2) the grid-based correction (GBC). The final improved positioning solution is then calculated by using the least square method (LSM) of the corrected pseudoranges. Kinematic test results in urban environments show that both variations of the proposed model can improve the positioning accuracy by 42.9% and 40.8% in horizontal, and by 60.1% and 63.3% in 3-D, respectively, compared to the positioning results obtained by the traditional method without pseudorange error corrections. The improvements are 41.1% and 38.9% in horizontal, and 45.7% and 50.0% in 3-D, respectively, compared with traditional elevation angle weighting method.

The pseudolite system is a good alternative for indoor positioning systems due to its large coverage area and accurate positioning solution. However, for common Global Positioning System (GPS) receivers, the pseudolite system requires some modifications of the user terminals. To solve the problem, this paper proposes a new pseudolite-based indoor positioning system architecture. The main idea is to receive real-world GPS signals, repeat each satellite signal and transmit those using indoor transmitting antennas. The transmitted GPS-like signal can be processed (signal acquisition and tracking, navigation data decoding) by the general receiver and thus no hardware-level modification on the receiver is required. In addition, all Tx can be synchronized with each other since one single clock is used in Rx/Tx. The proposed system is simulated using a software GPS receiver. The simulation results show the indoor positioning system is able to provide high accurate horizontal positioning in both static and dynamic situations.