A Positioning System in an Urban Vertical Heterogeneous Network (VHetNet)

Global navigation satellite systems (GNSSs) are essential in providing localization and navigation services to most of the world due to their superior coverage. However, due to high pathloss and inevitable atmospheric effect, the positioning performance of any standalone GNSS is still poor in urban areas. To improve the positioning performance of legacy GNSSs in urban areas, a positioning system, which utilizes high altitude platform station (HAPS) and 5G gNodeBs (gNBs), in a futuristic urban vertical heterogeneous network (VHetNet) is proposed. In this paper, we demonstrate the effectiveness of gNBs in improving the vertical positioning accuracy for both the GPS-only system and the HAPS-aided GPS system by analyzing the impact of the density of gNBs and the pseudorange error of gNB on the positioning performance of the gNB augmented positioning systems. We also demonstrate the effectiveness of receiver autonomous integrity monitoring (RAIM) algorithms on the HAPS and/or gNB aided GPS systems in urban areas

GNSS Signal Demodulation Performance in Urban Environments

International audienceSatellite navigation signals demodulation performance is historically tested and compared in the Additive White Gaussian Noise propagation channel model which well simulates open areas. Nowadays, the majority of new applications targets dynamic users in urban environments; therefore the implementation of a simulation tool able to provide realistically GNSS signal demodulation performance in obstructed propagation channels has become mandatory . This paper presents the simulator SiGMeP (Simulator for GNSS Message Performance) which is wanted to provide demodulation performance of any GNSS signals in urban environment , as faithfully of reality as possible . The demodulation performance of GPS L1C/A, GPS L2C, GPS L1C and Galileo E1 OS signals simulated with SiGMeP in the AWGN channel model configuration is firstly showed . Then, the demodulation performance of GPS L1C simulated with SiGMeP in urban environments is presented using the Prieto channel model with two signal carrier phase estimation configurations: perfect signal carrier phase estimation and PLL trackin

Aiding GPS with Additional Satellite Navigation Services

In modern warfare navigation services are very important. GPS is currently providing service for accurate navigation, except in some areas, especially urban areas, where GPS signals cannot always be tracked by users. In these cases some additional navigation support could be provided by other global navigation satellite systems. If GPS is combined with other navigation systems than the navigation gap will be minor. In this thesis, the effect of combining GPS with other satellite navigation systems, specifically GLONASS, Galileo and Compass, is evaluated in terms of availability and position dilution of precision (PDOP) values. First, satellite constellations are simulated in Satellite Tool Kit (STK) to generate ephemeris data. A street scenario is then established for simulating different elevation mask angles to represent urban and mountainous areas. The performance of the combined system is also evaluated as a function of the uncertainty in the time offset between systems. Combined GPS/GLONASS and GPS/Compass solutions showed little improvement for low elevation mask angles, however they provided some enhancement for higher elevation angles. Combined GPS/Galileo performance was improved for all elevation angles compared to only GPS, GPS/GLONASS, and GPS/Compass. The best results for availability and PDOP were obtained from combining all four systems. Although using satellites from other constellations enhances availability and decreases errors. It also brings dependency on other systems other than GPS. Adding two satellites from only the Galileo constellation to GPS is shown to be a configuration with a good compromise between dependency and performance

Vision for mobile robot localization in urban environments

This paper addresses the problem of mobile robot localization in urban environments. Typically, GPS is the preferred sensor for outdoor operation. However, using GPS-only localization methods leads to significant performance degradation in urban areas where tall nearby structures obstruct the clear view of the satellites. In our work, we use vision-based techniques to supplement GPS and odometry and provide accurate localization. The vision system identifies prominent linear features in the scene and matches them with a reduced model of nearby buildings, yielding improved pose estimation of the robot

Demodulation Performance Assessment of New GNSS Signals in Urban Environments

International audienceSatellite navigation signals demodulation performance ishistorically tested and compared in the Additive WhiteGaussian Noise propagation channel model which wellsimulates the signal reception in open areas. Nowadays,the majority of new applications targets dynamic users inurban environments; therefore the GNSS signalsdemodulation performance has become mandatory to beprovided in urban environments. The GPS L1C signaldemodulation performance in urban environments is thusprovided in this paper. To do that, a new methodologyadapted to provide and assess GNSS signalsdemodulation performance in urban channels has beendeveloped. It counteracts the classic method limitationswhich are the fluctuating received C/N0 in urbanenvironments and the fact that each received message istaken into account in the error rate computation whereasin GNSS it is not necessary. The new methodology thusproposes to provide the demodulation performance for‘favorable’ reception conditions together with statisticalinformation about the occurrence of these favorablereception conditions. To be able to apply this newmethodology and to provide the GPS L1C signaldemodulation performance in urban environments, asimulator SiGMeP (Simulator for GNSS MessagePerformance) has been developed. Two urbanpropagation channel models can be tested: thenarrowband Perez-Fontan/Prieto model and the widebandDLR model. Moreover, the impact of the received signalphase estimation residual errors has been taken intoaccount (ideal estimation is compared with PLL tracking)

A Fuzzy set-based method to identify the car position in a road lane at intersections by smartphone GPS data

Abstract Intelligent transportation systems (ITS) work by collections of data in real time. Average speed, travel time and delay at intersections are some of the most important measures, often used for monitoring the performance of transportation systems, and useful for system management and planning. In urban transportation planning, intersections are usually considered critical points, acting as bottlenecks and clog points for urban traffic. Thus, detecting the travel time at intersections in different turning directions is an activity useful to improve the urban transport efficiency. Smartphones represent a low-cost technology, with which is possible to obtain information about traffic state. However, smartphone GPS data suffer for low precision, mainly in urban areas. In this paper, we present a fuzzy set-based method for car positioning identification within road lanes near intersections using GPS data coming from smartphones. We have introduced the fuzzy sets to take into account uncertainty embedded in GPS data when trying to identify the position of cars within the road lanes. Moreover, we introduced a Genetic Algorithm to calibrate the fuzzy parameters in order to obtain a novel supervised clustering technique. We applied the proposed method to one intersection in the urban road network of Bari (Italy). First results reveal the effectiveness of the proposed methodology when comparing the outcomes of the proposed method with two well-known clustering techniques (Fuzzy C-means, K-means)

Multi-Frequency Precise Point Positioning using GPS and Galileo data with smoothed ionospheric corrections

The poor signal visibility and continuity associated with urban environments together with the slow convergence/reconvergence time of Precise Point Positioning (PPP), usually makes PPP unsuitable for land navigation in cities. However, results based on simulated open areas demonstrated that, once Galileo reaches final operational capability, PPP convergence time will be cut in a half using dual-constellation GPS/Galileo observations. Therefore, it might be possible to extend the applicability of PPP to land navigation in certain urban areas. Preliminary results, based on simulations, showed that GPS/Galileo PPP is possible where buildings are relatively short and satellites minimum visibility requirement is met for most of the time. In urban environments, signal discontinuity and reconvergence still represent the major problem for traditional PPP, which is based on the ionosphere-free combination of two-frequency pseudo-range and carrier phase. An alternative method to mitigate the ionosphere delay is proposed in order to ensure the best positioning performance from multi-frequency PPP. Instead of using the ionosphere-free combination, here low noise dual- or triple-frequency pseudo-range combinations are corrected with ionosphere delay information coming from federated carrier smoothing (Hatch) iono-estimation filters for each satellite. This method provides faster re- convergence time and ensures the best possible positioning performance from the Galileo Alternative BOC modulation in multi-frequency PPP. Indeed, even though Galileo E5 has small tracking noise and excellent multipath rejection, its PPP positioning performance is limited by the influence of E1 signal errors in the ionosphere-free combination, degrading the quality of the measurements

Map-matching in complex urban road networks

Global Navigation Satellite Systems (GNSS) such as GPS and digital road maps can be used for land vehicle navigation systems. However, GPS requires a level of augmentation with other navigation sensors and systems such as Dead Reckoning (DR) devices, in order to achieve the required navigation performance (RNP) in some areas such as urban canyons, streets with dense tree cover, and tunnels. One of the common solutions is to integrate GPS with DR by employing a Kalman Filter (Zhao et al., 2003). The integrated navigation systems usually rely on various types of sensors. Even with very good sensor calibration and sensor fusion technologies, inaccuracies in the positioning sensors are often inevitable. There are also errors associated with spatial road network data. This paper develops an improved probabilistic Map Matching (MM) algorithm to reconcile inaccurate locational data with inaccurate digital road network data. The basic characteristics of the algorithm take into account the error sources associated with the positioning sensors, the historical trajectory of the vehicle, topological information on the road network (e.g., connectivity and orientation of links), and the heading and speed information of the vehicle. This then enables a precise identification of the correct link on which the vehicle is travelling. An optimal estimation technique to determine the vehicle position on the link has also been developed and is described. Positioning data was obtained from a comprehensive field test carried out in Central London. The algorithm was tested on a complex urban road network with a high resolution digital road map. The performance of the algorithm was found to be very good for different traffic maneuvers and a significant improvement over using just an integrated GPS/DR solution

Achieving genuinely dynamic road user charging : issues with a GNSS-based approach

Peer reviewedPostprin

Synchronous LoRa mesh network to monitor processes in underground infrastructure

Collecting precise real-time information on urban drainage system performance is essential to identify, predict, and manage critical loading situations, such as urban flash floods and sewer overflows. Although emerging low-power wireless communication techniques allow efficient data transfers with great above-ground performance, for underground or indoor applications in a large coverage range are difficult to achieve due to physical and topological limitations, particularly in dense urban areas. In this paper, we first discuss the range limitations of the LoRaWAN standard based on a systematic evaluation of a long-term operation of a sensor network monitoring in-sewer process dynamics. Analyses reveal an-on average-five-fold higher data packet loss for sub-surface nodes, which steadily grows with increasing distance to the gateway. Second, we present a novel LPWAN concept based on the LoRa technology that enhances transmission reliability, efficiency, and flexibility in range-critical situations through meshed multi-hop routing and ensures a precise time-synchronization through optional GPS or DCF77 long-wave time signaling. Third, we illustrate the usefulness of the newly developed concept by evaluating the radio transmission performance for two independent full-scale field tests. Test results show that the synchronous LoRa mesh network approach clearly outperforms the standard LoRaWAN technique with regard to the reliability of packet delivery when transmitting from range-critical locations. Hence, the approach is expected to generally ease data collection from difficult-to-access locations such as underground areas