Paul D. Groves

Shadow Matching: A New GNSS Positioning Technique for Urban Canyons

The Global Positioning System (GPS) is unreliable in dense urban areas, known as urban canyons, which have tall buildings or narrow streets. This is because the buildings block the signals from many of the satellites. Combining GPS with other Global Navigation Satellite Systems (GNSS) significantly increases the availability of direct line-of-sight signals. Modelling is used to demonstrate that, although this will enable accurate positioning along the direction of the street, the positioning accuracy in the cross-street direction will be poor because the unobstructed satellite signals travel along the street, rather than across it. A novel solution to this problem is to use 3D building models to improve cross-track positioning accuracy in urban canyons by predicting which satellites are visible from different locations and comparing this with the measured satellite visibility to determine position. Modelling is used to show that this shadow matching technique has the potential to achieve metre-order cross-street positioning in urban canyons. The issues to be addressed in developing a robust and practical shadow matching positioning system are then discussed and solutions proposed.

Multi-Constellation GNSS Performance Evaluation for Urban Canyons Using Large Virtual Reality City Models

Positioning using the Global Positioning System (GPS) is unreliable in dense urban areas with tall buildings and/or narrow streets, known as ‘urban canyons’. This is because the buildings block, reflect or diffract the signals from many of the satellites. This paper investigates the use of 3-Dimensional (3-D) building models to predict satellite visibility. To predict Global Navigation Satellite System (GNSS) performance using 3-D building models, a simulation has been developed. A few optimized methods to improve the efficiency of the simulation for real-time purposes were implemented. Diffraction effects of satellite signals were considered to improve accuracy. The simulation is validated using real-world GPS and GLObal NAvigation Satellite System (GLONASS) observations. The performance of current and future GNSS in urban canyons is then assessed by simulation using an architectural city model of London with decimetre-level accuracy. GNSS availability, integrity and precision is evaluated over pedestrian and vehicle routes within city canyons using different combinations of GNSS constellations. The results show that using GPS and GLONASS together cannot guarantee 24-hour reliable positioning in urban canyons. However, with the addition of Galileo and Compass, currently under construction, reliable GNSS performance can be obtained at most, but not all, of the locations in the test scenarios. The modelling also demonstrates that GNSS availability is poorer for pedestrians than for vehicles and verifies that cross-street positioning errors are typically larger than along-street due to the geometrical constraints imposed by the buildings. For many applications, this modelling technique could also be used to predict the best route through a city at a given time, or the best time to perform GNSS positioning at a given location.

Height Aiding, C/N 0 Weighting and Consistency Checking for GNSS NLOS and Multipath Mitigation in Urban Areas

Multiple global navigation satellite system (GNSS) constellations can dramatically improve the signal availability in dense urban environments. However, accuracy remains a challenge because buildings block, reflect and diffract the signals. This paper investigates three different techniques for mitigating the impact of non-line-of-sight (NLOS) reception and multipath interference on position accuracy without using additional hardware, testing them using data collected at multiple sites in central London. Aiding the position solution using a terrain height database was found to have the biggest impact, improving the horizontal accuracy by 35% and the vertical accuracy by a factor of 4. An 8% improvement in horizontal accuracy was also obtained from weighting the GNSS measurements in the position solution according to the carrier-power-to-noise-density ratio (C/N0). Consistency checking using a conventional sequential elimination technique was found to degrade horizontal positioning performance by 60% because it often eliminated the wrong measurements in cases when multiple signals were affected by NLOS reception or strong multipath interference. A new consistency checking method that compares subsets of measurements performed better, but was still equally likely to improve or degrade the accuracy. This was partly because removing a poor measurement can result in adverse signal geometry, degrading the position accuracy. Based on this, several ways of improving the reliability of consistency checking are proposed.

NLOS GPS signal detection using a dual-polarisation antenna

The reception of indirect signals, either in the form of non-line-of-sight (NLOS) reception or multipath interference, is a major cause of GNSS position errors in urban environments. We explore the potential of using dual-polarisation antenna technology for detecting and mitigating the reception of NLOS signals and severe multipath interference. The new technique computes the value of the carrier-power-to-noise-density (C/N0) measurements from left-hand circular polarised outputs subtracted from the right-hand circular polarised C/N0 counterpart. If this quality is negative, NLOS signal reception is assumed. If the C/N0 difference is positive, but falls below a threshold based on its lower bound in an open-sky environment, severe multipath interference is assumed. Results from two experiments are presented. Open-field testing was first performed to characterise the antenna behaviour and determine a suitable multipath detection threshold. The techniques were then tested in a dense urban area. Using the new method, two signals in the urban data were identified as NLOS-only reception during the occupation period at one station, while the majority of the remaining signals present were subject to a mixture of NLOS reception and severe multipath interference. The point positioning results were dramatically improved by excluding the detected NLOS measurements. The new technique is suited to a wide range of static ground applications based on our results.

Smartphone Shadow Matching for Better Cross-street GNSS Positioning in Urban Environments

Global Navigation Satellite System (GNSS) shadow matching is a new positioning technique that determines position by comparing the measured signal availability and strength with predictions made using a three-dimensional (3D) city model. It complements conventional GNSS positioning and can significantly improve cross-street positioning accuracy in dense urban environments. This paper describes how shadow matching has been adapted to work on an Android smartphone and presents the first comprehensive performance assessment of smartphone GNSS shadow matching. Using GPS and GLONASS data recorded at 20 locations within central London, it is shown that shadow matching significantly outperforms conventional GNSS positioning in the cross-street direction. The success rate for obtaining a cross-street position accuracy within 5 m, enabling the correct side of a street to be determined, was 54·50% using shadow matching, compared to 24·77% for the conventional GNSS position. The likely performance of four-constellation shadow matching is predicted, the feasibility of a large-scale implementation of shadow matching is assessed, and some methods for improving performance are proposed. A further contribution is a signal-to-noise ratio analysis of the direct line-of-sight and non-line-of-sight signals received on a smartphone in a dense urban environment.

GNSS multipath detection using three-frequency signal-to-noise measurements

Abstract A new technique for detecting GNSS multipath interference by comparing signal-to-noise (SNR) measurements on three frequencies is presented. Depending on the phase lag of the reflected signal with respect to the direct signal, multipath interference can be either constructive or destructive, with a commensurate effect on the measured SNR. However, as the phase lag is frequency dependent, the SNR is perturbed differently on each frequency. Thus, by differencing SNR measurements on different frequencies and comparing the result with that obtained in a low-multipath environment, multipath can be detected. Using three frequencies makes the process more robust. A three-frequency SNR-based multipath detector has been developed and calibrated using measurements from GPS Block IIF satellites in a low-multipath environment. The new detector has been tested in a range of urban environments and its multipath detection capability verified by showing that the MP observables oscillate when the new detection statistic is above a threshold value determined using data collected in a low-multipath environment. The new detector is also sensitive to diffraction.

The Complexity Problem in Future Multisensor Navigation and Positioning Systems: A Modular Solution

Navigation and positioning system users are demanding greater accuracy and reliability in ever more challenging environments. This is driving a wave of rapid innovation with the result that multisensor integrated navigation systems will become much more complex. This introduces a number of problems, including how to find the necessary expertise to integrate a diverse range of technologies, how to combine technologies from different organisations that wish to protect their intellectual property, and how to incorporate new navigation technologies and methods without having to redesign the whole system. It also makes it desirable to share development effort over a range of different applications. To address this, the feasibility of a modular approach to the design and development of multisensor integrated navigation and positioning systems is analysed. Assessments of the requirements of different user communities and the adaptability of the different navigation and positioning technologiesto different contexts and requirements are presented. Based on this, the adoption of an open interface standard for modular integration is recommended and the issues to be resolved in developing that standard are outlined.

Navigation using inertial sensors [Tutorial]

This tutorial provides an introduction to navigation using inertial sensors, explaining the underlying principles. Topics covered include accelerometer and gyroscope technology and their characteristics, strapdown inertial navigation, attitude determination, integration and alignment, zero updates, motion constraints, pedestrian dead reckoning using step detection, and fault detection.

The four key challenges of advanced multisensor navigation and positioning

The next generation of navigation and positioning systems must provide greater accuracy and reliability in a range of challenging environments to meet the needs of a variety of mission-critical applications. No single navigation technology is robust enough to meet these requirements on its own, so a multisensor solution is required. Although many new navigation and positioning methods have been developed in recent years, little has been done to bring them together into a robust, reliable, and cost-effective integrated system. To achieve this, four key challenges must be met: complexity, context, ambiguity, and environmental data handling. This paper addresses each of these challenges. It describes the problems, discusses possible approaches, and proposes a program of research and standardization activities to solve them. The discussion is illustrated with results from research into urban GNSS positioning, GNSS shadow matching, environmental feature matching, and context detection.

Intelligent urban positioning, shadow matching and non-line-of-sight signal detection

High sensitivity receivers and multiple satellite constellations have vastly improved GNSS signal availability in dense urban areas. However, accuracy remains a problem due to the blockage and reflection of many of the signals by buildings and other obstacles. Reliable metres-level positioning in dense urban areas is difficult to achieve cost-effectively using a single technology. The way forward is to combine multiple positioning techniques. Intelligent urban positioning (IUP) aims to achieve this level of performance by combining positioning algorithms augmented with three-dimensional mapping; techniques for distinguishing between NLOS and LOS signals; and multi-constellation GNSS, using signals from all visible satellites. This paper reviews non-line-of-sight (NLOS) signal detection and presents results of a new C/N0-weighted consistency checking method. It describes and presents results of shadow matching, a new method using a 3D city model to improve cross-street GNSS positioning accuracy. Finally, a method for combining the different components of IUP is presented together with the results of a preliminary demonstration of the IUP concept using GPS and GLONASS data collected in London.