Design and Testing of a Multi-Sensor Pedestrian Location and Navigation Platform

Navigation and location technologies are continually advancing, allowing ever higher accuracies and operation under ever more challenging conditions. The development of such technologies requires the rapid evaluation of a large number of sensors and related utilization strategies. The integration of Global Navigation Satellite Systems (GNSSs) such as the Global Positioning System (GPS) with accelerometers, gyros, barometers, magnetometers and other sensors is allowing for novel applications, but is hindered by the difficulties to test and compare integrated solutions using multiple sensor sets. In order to achieve compatibility and flexibility in terms of multiple sensors, an advanced adaptable platform is required. This paper describes the design and testing of the NavCube, a multi-sensor navigation, location and timing platform. The system provides a research tool for pedestrian navigation, location and body motion analysis in an unobtrusive form factor that enables in situ data collections with minimal gait and posture impact. Testing and examples of applications of the NavCube are provided

Navigation Recommender:Real-Time iGNSS QoS Prediction for Navigation Services

Global Navigation Satellite Systems (GNSSs), especially Global Positioning System (GPS), have become commonplace in mobile devices and are the most preferred geo-positioning sensors for many location-based applications. Besides GPS, other GNSSs under development or deployment are GLONASS, Galileo, and Compass. These four GNSSs are planned to be integrated in the near future. It is anticipated that integrated GNSSs (iGNSSs) will improve the overall satellite-based geo-positioning performance. However, one major shortcoming of any GNSS and iGNSSs is Quality of Service (QoS) degradation due to signal blockage and attenuation by the surrounding environments, particularly in obstructed areas. GNSS QoS uncertainty is the root cause of positioning ambiguity, poor localization performance, application freeze, and incorrect guidance in navigation applications. In this research, a methodology, called iGNSS QoS prediction, that can provide GNSS QoS on desired and prospective routes is developed. Six iGNSS QoS parameters suitable for navigation are defined: visibility, availability, accuracy, continuity, reliability, and flexibility. The iGNSS QoS prediction methodology, which includes a set of algorithms, encompasses four modules: segment sampling, point-based iGNSS QoS prediction, tracking-based iGNSS QoS prediction, and iGNSS QoS segmentation. Given that iGNSS QoS prediction is data- and compute-intensive and navigation applications require real-time solutions, an efficient satellite selection algorithm is developed and distributed computing platforms, mainly grids and clouds, for achieving real-time performance are explored. The proposed methodology is unique in several respects: it specifically addresses the iGNSS positioning requirements of navigation systems/services; it provides a new means for route choices and routing in navigation systems/services; it is suitable for different modes of travel such as driving and walking; it takes high-resolution 3D data into account for GNSS positioning; and it is based on efficient algorithms and can utilize high-performance and scalable computing platforms such as grids and clouds to provide real-time solutions. A number of experiments were conducted to evaluate the developed methodology and the algorithms using real field test data (GPS coordinates). The experimental results show that the methodology can predict iGNSS QoS in various areas, especially in problematic areas

A Survey of 3D Indoor Localization Systems and Technologies

Indoor localization has recently and significantly attracted the interest of the research community mainly due to the fact that Global Navigation Satellite Systems (GNSSs) typically fail in indoor environments. In the last couple of decades, there have been several works reported in the literature that attempt to tackle the indoor localization problem. However, most of this work is focused solely on two-dimensional (2D) localization, while very few papers consider three dimensions (3D). There is also a noticeable lack of survey papers focusing on 3D indoor localization; hence, in this paper, we aim to carry out a survey and provide a detailed critical review of the current state of the art concerning 3D indoor localization including geometric approaches such as angle of arrival (AoA), time of arrival (ToA), time difference of arrival (TDoA), fingerprinting approaches based on Received Signal Strength (RSS), Channel State Information (CSI), Magnetic Field (MF) and Fine Time Measurement (FTM), as well as fusion-based and hybrid-positioning techniques. We provide a variety of technologies, with a focus on wireless technologies that may be utilized for 3D indoor localization such as WiFi, Bluetooth, UWB, mmWave, visible light and sound-based technologies. We critically analyze the advantages and disadvantages of each approach/technology in 3D localization

Seamless Positioning and Navigation in Urban Environment

L'abstract è presente nell'allegato / the abstract is in the attachmen

Advanced Location-Based Technologies and Services

Since the publication of the first edition in 2004, advances in mobile devices, positioning sensors, WiFi fingerprinting, and wireless communications, among others, have paved the way for developing new and advanced location-based services (LBSs). This second edition provides up-to-date information on LBSs, including WiFi fingerprinting, mobile computing, geospatial clouds, geospatial data mining, location privacy, and location-based social networking. It also includes new chapters on application areas such as LBSs for public health, indoor navigation, and advertising. In addition, the chapter on remote sensing has been revised to address advancements

Hybrid and Cooperative Positioning Solutions for Wireless Networks

In this thesis, some hybrid and cooperative solutions are proposed and analyzed to locate the user in challenged scenarios, with the aim to overcome the limits of positioning systems based on single technology. The proposed approaches add hybrid and cooperative features to some conventional position estimation techniques like Kalman filter and particle filter, and fuse information from different radio frequency technologies. The concept of cooperative positioning is enhanced with hybrid technologies, in order to further increase the positioning accuracy and availability. In particular, wireless sensor networks and radio frequency identification technology are used together to enhance the collected data with position information. Terrestrial ranging techniques (i.e., ultra-wide band technology) are employed to assist the satellite-based localization in urban canyons and indoors. Moreover, some advanced positioning algorithms, such as energy efficient, cognitive tracking and non-line-of-sight identification, are studied to satisfy the different positioning requirements in harsh indoor environments. The proposed hybrid and cooperative solutions are tested and verified by first Monte Carlo simulations then real experiments. The obtained results demonstrate that the proposed solutions can increase the robustness (positioning accuracy and availability) of the current localization system

Pedestrian real-time location and routing information delivered to mobile digital architectural guides

The work described in this thesis deals with two particular issues relating to the effective delivery of Architectural information that includes textual, 2D graphics and 3D graphic information to small mobile digital devices on location. These issues were investigated, and a solution was suggested in this thesis as part of an ongoing research project, 'City in the Palm of your Hand', that is being applied in the city of Liverpool, UK. The outcomes have broader implications for other applications of the theories and technologies related to pedestrian guides

DoA and ToA Estimation, Device Positioning and Network Synchronization in 5G New Radio : Algorithms and Performance Analysis

Location information plays a significant role not only in our everyday life through various location-based services, but also in emerging technologies such as virtual reality, robotics, and autonomous driving. In contrast to the existing and earlier cellular generations, positioning has been considered as a key element in future cellular networks from the very beginning of the fifth generation (5G) standardization process. Even though the earlier generations are capably of providing coarse location estimates, the achieved accuracy is far from the expected even sub-meter positioning accuracy envisioned in the context of 5G networks. In general, 5G new radio (NR) networks provide a convenient infrastructure for positioning by means of wider bandwidths, larger antenna arrays, and even more densely deployed networks especially at high millimeter wave (mmWave) frequencies. Building on dense 5G NR networks, this thesis focuses on the development of novel network-centric positioning frameworks by exploiting the existing NR reference signals. The contributions in this thesis can be grouped into topics based on the considered frequency ranges and the employed beamforming (BF) schemes therein. First, novel cascaded algorithms for sequential device positioning are proposed assuming 5G NR networks operating at the lower sub-6 GHz frequency range and equipped with digital BF capabilities. In the first stage of the cascaded solution, two sequential estimators are proposed for joint direction of arrival (DoA) and time of arrival (ToA) estimation facilitating the received reference signals. Thereafter, the second-stage sequential estimators employing the obtained DoA and ToA estimates are proposed for joint positioning and network synchronization resulting in not only device location estimates, but also clock parameter estimates that are obtained as a valuable by-product. Such a choice stems from the fact that the ToA estimates are not feasible for positioning as such due to the clock instabilities in low-cost devices and the insufficient level of synchronization in the cellular networks. Second, a similar cascaded algorithm for joint positioning and network synchronization is proposed in the context of dense mmWave 5G networks and fundamentally different analog BFs. In particular, a novel joint DoA and ToA estimator is proposed by fusing information from multiple received beams based on a novel beam-selection method. In addition, the theoretical performance limits are derived and compared to those obtained using the digital BFs. The cascaded framework is completed with the second-stage positioning solution in a similar manner as in the case of digital BFs. The performance of both frameworks is evaluated and analyzed in various scenarios using extensive computer simulations relying on the latest 5G NR numerology and a ray-tracing tool. Overall, this thesis provides valuable insights into practical positioning algorithms and their performance when relying solely on the 5G NR networks and available signalling therein. The obtained results in this thesis indicate that the envisioned sub-meter positioning accuracy is technically feasible using NR-based solutions