Ziyi Jiang's research while affiliated with Kingston College United Kingdom and other places

BIOGRAPHY Paul Groves is a Lecturer (academic faculty member) in GNSS, Navigation and Location Technology at University College London (UCL). He was a navigation systems researcher at QinetiQ from 1997 to 2009. He is interested in all aspects of navigation and positioning, including multi-sensor integrated navigation and robust GNSS under challenging reception conditions. He is an author of more than 30 technical publications, including the book, Principles of GNSS, Inertial and Multi-Sensor Integrated Navigation Systems (Artech House). He holds a BA/MA and a DPhil in physics from the University of Oxford. He is a Fellow of the Royal Institute of Navigation and chairs its R&D group. He is also an associate editor of Navigation: Journal of the ION. (p.groves@ucl.ac.uk) Ziyi Jiang is a Research Fellow at UCL, currently specialising in multipath mitigation research. He has recently submitted his PhD thesis on digital route model aided integrated satellite navigation and low-cost inertial sensors for high-performance positioning on the railways. He holds a BEng in measuring and control technology from Harbin Engineering University, China. Benjamin Skelton is completing a MSc in surveying at UCL, including a research project studying dual-polarization GNSS antennas. He holds a LLB in Law from the University of Leicester, UK. He appears in Figure 3.

The coming requirements of greater accuracy and reliability in a range of challenging environments for a multitude of missioncritical applications require a multisensor approach and an over-arching methodology that does not yet exist. The likelihood depends on both the positioning method and the context, both environmental and behavioral. Urban and indoor positioning techniques that do not require dedicated infrastructure are particularly vulnerable to ambiguity. Even where a signal of opportunity is identifiable, the transmission site may change without warning. For example, Wi-Fi access points are sometimes moved and mobile phone networks are periodically refigured. Thus, there is a risk of false landmark identification. The pattern-matching positioning method maintains a database of measurable parameters that vary with position. Examples include terrain height, magnetic field variations, Wi-Fi signal strengths, and GNSS signal availability information.

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.

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/N 0) measurements from left-hand circular polarised outputs subtracted from the right-hand circular polarised C/N 0 counterpart. If this quality is negative, NLOS signal reception is assumed. If the C/N 0 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.

Non-line-of-sight (NLOS) reception and multipath interference are major causes of poor GNSS positioning accuracy in urban environments. This paper describes three pieces of work to mitigate their effects: a new multipath detection technique using multi-frequency carrier-power-to-noise-density ratio (C/N0) measurements; the first multi-constellation test of the dual-polarization NLOS detection technique; and a proposal for a portfolio approach to multipath and NLOS mitigation. Constructive multipath interference results in an increase in C/N0, whereas destructive interference results in a decrease. As the phase of a reflected signal with respect to its directly received counterpart depends on the wavelength, the multipath interference may be constructive on one frequency and destructive on another. Thus, by comparing the difference in measured C/N0 between two frequencies with what is normally expected for that signal at that elevation angle, strong multipath interference may be detected. A new multipath detection technique based on this principle is demonstrated using data collected in an urban environment. The dual-polarization NLOS detection technique separately correlates the right hand circularly polarized (RHCP) and left hand circularly polarized (LHCP) outputs of a dual-polarization antenna and differences the C/N0 measurements. The result is positive for directly received signals and negative for most NLOS signals. Here, this technique is demonstrated on GLONASS signals for the first time and the effect of removing an NLOS signal from the position solution is assessed. Finally, a qualitative assessment and comparison of 18 different classes of technique for mitigating and detecting NLOS reception and multipath interference is presented, considering ease of implementation and performance. It is concluded that, for most applications, no one technique is completely effective. A portfolio approach is therefore proposed in which multiple techniques are combined. Suitable portfolios are then proposed for professional-grade and for consumer-grade user equipment.

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.

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.

Reliable metres-level positioning in dense urban areas is difficult to achieve cost-effectively using a single method. The way forward is to combine multiple positioning techniques. This paper introduces the concept of intelligent urban positioning (IUP), which combines • Multi-constellation GNSS; • Multiple techniques for detecting non-line-of-sight (NLOS) signal propagation; and • Multiple techniques using three-dimensional mapping. IUP may also be extended to incorporate other position-fixing and dead-reckoning sensors. The paper begins by explaining the limitations of conventional GNSS positioning in dense urban environments. It then introduces the potential ingredients of intelligent urban positioning, a mixture of new and established techniques, and discusses how they might be combined. 3D mapping may be used for conventional map matching, height aiding, NLOS signal detection, reflection prediction and shadow matching, a new method for determining position by comparing measured and predicted satellite visibility. NLOS reception may also be detected using consistency checking, C/N0 measurement, dual-polarization antenna technology, an antenna array and a sky-pointing camera. The results of a preliminary demonstration of the IUP concept using GPS and GLONASS data collected in London are then presented. In this test, conventional GNSS positioning, aided by consistency-based LOS detection is combined with shadow matching. In the example presented, a horizontal position error of less than 2m was obtained, compared to about 25m for conventional GNSS positioning. This clearly demonstrates the potential of the IUP approach. Note, however, that further research is needed to improve the reliability.

High sensitivity multi-constellation GNSS receivers can dramatically improve the satellite availability in an urban environment. However, positioning accuracy remains a challenge because of blockage, reflection and diffraction of signals by buildings. In typical urban positioning scenarios, the receiver often receives a mixture of non-line-of-sight (NLOS) signals, multipath-contaminated direct line-of-sight (LOS) signals, and clean direct-LOS signals. Multi-constellation GNSS allows maximising the positioning accuracy by selecting only those signals that are least contaminated by multipath and NLOS propagation to form the navigation solution. A technique exploring the consistency among received signals using randomly draw subsets of all available signals is proposed in this research. The implementation of the algorithm follows an estimation scheme known as RANdom SAmple Consensus (RANSAC). A pre-defined cost function is firstly used to select the best available subset of measurements. A reference solution is produced from the best available subset. The “residuals” of all received signals, i.e. the differences between the observed measurements and the predictions from the reference solution, are examined. The examination features a receiver autonomous integrity monitoring (RAIM) like statistical test based on specific distributions. A final solution is produced from measurements passed the examination plus the best available subset. In addition, height aiding from a terrain elevation database is used as an additional ranging measurement to further enhance the positioning performance. Two GPS/GLONASS data sets collected from different urban areas of central London were used for testing. Different versions of the cost function and the effect of introducing height aiding are tested. The results show an improvement of positioning accuracy over conventional least-squares algorithm and previous consistency-checking algorithm through reduction of the impact of multipath and NLOS propagation errors.

In a typical urban environment, a mixture of multipath-free, multipath-contaminated and non-line-of-sight (NLOS) propagated GNSS signals are received. The errors caused by multipath-contaminated and NLOS reception are the dominant source of reduced consumer-grade positioning accuracy in the urban environment. Many conventional receiver-based and antenna-based techniques have been developed to mitigate either multipath or NLOS reception with mixed success. Nevertheless, the positioning accuracy can be maximised based on the simple principle of selecting only those signals least contaminated by multipath and NLOS propagation to form the navigation solution. The advent of multi-constellation GNSS provides the opportunity to realise this technique that is potentially low-cost and effective for consumer-grade devices. It may also be implemented as an augmentation to other multipath mitigation techniques. The focus of this paper is signal selection by consistency checking, whereby measurements from different satellites are compared with each other to identify the NLOS and most multipath-contaminated signals. The principle of consistency checking is that multipath-contaminated and NLOS measurements produce a less consistent navigation solution than multipath-free measurements. RAIM-based fault detection operates on the same principle. Three consistency-checking schemes based on single-epoch least-squares residuals are assessed: single sweep, recursive checking and a hybrid version of the first two. Two types of weighting schemes are also considered: satellite elevation-based and signal C/N0-based weighting. The paper also discussed the different observables that may be used by a consistency-checking algorithm for different applications and their effect on detection sensitivity. Test results for the proposed algorithms are presented using data from both static positioning and stand-alone dynamic positioning experiments. The static data was collected using a pair of survey-grade multi-constellation GNSS receivers using both GPS and GLONASS signals at open sky and urban canyon locations, while the dynamic data was collected using a consumer-grade GPS/GLONASS receiver on a car in a mixed urban environment. Significant improvements in position domain are demonstrated using the weighted recursive methods in the open environments. However in the urban environments, there are insufficient directly received signals for the conventional RAIM-based signal selection to be effective all the time. Both positioning improvements and risky outliers are demonstrated. More advanced techniques have been identified for investigation in future research.