Hybridisation of GNSS with other wireless/sensors technologies onboard smartphones to offer seamless outdoors-indoors positioning for LBS applications

Location-based services (LBS) are becoming an important feature on today’s smartphones (SPs) and tablets. Likewise, SPs include many wireless/sensors technologies such as: global navigation satellite system (GNSS), cellular, wireless fidelity (WiFi), Bluetooth (BT) and inertial-sensors that increased the breadth and complexity of such services. One of the main demand of LBS users is always/seamless positioning service. However, no single onboard SPs technology can seamlessly provide location information from outdoors into indoors. In addition, the required location accuracy can be varied to support multiple LBS applications. This is mainly due to each of these onboard wireless/sensors technologies has its own capabilities and limitations. For example, when outdoors GNSS receivers on SPs can locate the user to within few meters and supply accurate time to within few nanoseconds (e.g. ± 6 nanoseconds). However, when SPs enter into indoors this capability would be lost. In another vain, the other onboard wireless/sensors technologies can show better SP positioning accuracy, but based on some pre-defined knowledge and pre-installed infrastructure. Therefore, to overcome such limitations, hybrid measurements of these wireless/sensors technologies into a positioning system can be a possible solution to offer seamless localisation service and to improve location accuracy. This thesis aims to investigate/design/implement solutions that shall offer seamless/accurate SPs positioning and at lower cost than the current solutions. This thesis proposes three novel SPs localisation schemes including WAPs synchronisation/localisation scheme, SILS and UNILS. The schemes are based on hybridising GNSS with WiFi, BT and inertial-sensors measurements using combined localisation techniques including time-of-arrival (TOA) and dead-reckoning (DR). The first scheme is to synchronise and to define location of WAPs via outdoors-SPs’ fixed location/time information to help indoors localisation. SILS is to help locate any SP seamlessly as it goes from outdoors to indoors using measurements of GNSS, synched/located WAPs and BT-connectivity signals between groups of cooperated SPs in the vicinity. UNILS is to integrate onboard inertial-sensors’ readings into the SILS to provide seamless SPs positioning even in deep indoors, i.e. when the signals of WAPs or BT-anchors are considered not able to be used. Results, obtained from the OPNET simulations for various SPs network size and indoors/outdoors combinations scenarios, show that the schemes can provide seamless and locate indoors-SPs under 1 meter in near-indoors, 2-meters can be achieved when locating SPs at indoors (using SILS), while accuracy of around 3-meters can be achieved when locating SPs at various deep indoors situations without any constraint (using UNILS). The end of this thesis identifies possible future work to implement the proposed schemes on SPs and to achieve more accurate indoors SPs’ location

Indoor location identification technologies for real-time IoT-based applications: an inclusive survey

YesThe advent of the Internet of Things has witnessed tremendous success in the application of wireless sensor networks and ubiquitous computing for diverse smart-based applications. The developed systems operate under different technologies using different methods to achieve their targeted goals. In this treatise, we carried out an inclusive survey on key indoor technologies and techniques, with to view to explore their various benefits, limitations, and areas for improvement. The mathematical formulation for simple localization problems is also presented. In addition, an empirical evaluation of the performance of these indoor technologies is carried out using a common generic metric of scalability, accuracy, complexity, robustness, energy-efficiency, cost and reliability. An empirical evaluation of performance of different RF-based technologies establishes the viability of Wi-Fi, RFID, UWB, Wi-Fi, Bluetooth, ZigBee, and Light over other indoor technologies for reliable IoT-based applications. Furthermore, the survey advocates hybridization of technologies as an effective approach to achieve reliable IoT-based indoor systems. The findings of the survey could be useful in the selection of appropriate indoor technologies for the development of reliable real-time indoor applications. The study could also be used as a reliable source for literature referencing on the subject of indoor location identification.Supported in part by the Tertiary Education Trust Fund of the Federal Government of Nigeria, and in part by the European Union’s Horizon 2020 Research and Innovation Programme under Grant agreement H2020-MSCA-ITN-2016 SECRET-72242

High integrity IMM-EKF based road vehicle navigation with low cost GPS/INS.

User requirements for the performance of GlobaL Navigation Satellite System (GNSS)-based road applications have been significantly increasing in recent years. Safety systems based on vehicle localization, electronic fee-collection systems, and traveler information services are just a few examples of interesting applications requiring onboard equipment (OBE) capable of offering a high available accurate position, even in unfriendly environments with low satellite visibility such as built-up areas or tunnels and at low cost. In addition to that, users and service providers demand from the OBEs not only accurate continuous positioning but integrity information of the reliability of this position as well. Specifically, in life-critical applications, high-integrity monitored positioning is absolutely required. This paper presents a solution based on the fusion of GNSS and inertial sensors (a Global Positioning System/Satellite-Based Augmentation System/Inertial Navigation System integrated system) running an extended Kalman filter combined with an interactive multimodel method (IMM-EKF). The solution developed in this paper supplies continuous positioning in marketable conditions and a meaningful trust level of the given solution. A set of tests performed in controlled and real scenarios proves the suitability of the proposed IMM-EKF implementation as compared with lowcost GNSS-based solutions, dead reckoning systems, single-model EKF, and other filtering approaches of the current literature.This work was supported in part by the Spanish Ministerio de Fomento under Grant FOM/3929/2005 and by the Galileo Joint Undertaking (GJU) under Grant GIROADS 332599. The Associate Editor for this paper was Y. Wang

Signals of Opportunity for Positioning Purposes

O ver the last years, location-based services (LBS) have become popular due to the emergence of smartphones with capabilities of positioning their user’s location on Earth at unprecedented speed and convenience. Behind such feat are the technological advances in global navigation satellite systems (GNSS), such as Galileo, Globalnaya Navigazionnaya Sputnikovaya Sistema (GLONASS), Global Positioning Service (GPS) and Beidou. The easiness of smartphones and the improvement of positioning technology has driven LBS to be at the core of many business models. Some of these business models rely on the user’s location to pick him up on a car, relinquish a meal to him, offer insights on sports performance, locate items to be picked up on a warehouse, among many others.While LBS are driving the need to continuously locate the user at higher degrees of accuracy and across any environment, be it in a city park, an urban canyon or inside a corporate office, some of these environments pose a challenge for GNSS. Indoor environments are particularly challenging for GNSS due to the attenuation and strong multipath imposed by walls and building materials. Such challenges and difficulties in signal acquisition have led to the development of solutions and technologies to improve positioning in indoor environments.While there are several commercial systems available to fulfill the needs of most LBS in indoor environments, most of these are not feasible to deploy at a global scale due to their infrastructure costs. Hence, several solutions have sought to build upon existing infrastructure to provide positioning information.Building upon existing infrastructure is what leads to the main topic of this thesis, the concept of signals of opportunity (SoO). A SoO is any wireless signal that can be exploited for a positioning purpose despite its initial design seeking to fulfill a different purpose. A few examples of these signals are IEEE 802.11 signals, commonly known as WiFi, Bluetooth, digital video broadcasting - terrestrial (DVB-T) and many of the cellular signals, such as long-term evolution (LTE), universal mobile telecommunications system (UMTS) and global mobile system (GSM).The goal of this thesis is to address various challenges related to SoO for positioning. From the identification of SoO at the physical layer, how to merge them at the algorithmic level and how to put them in use for a cognitive positioning system (CPS)

Indoor Positioning with GNSS-Like Local Signal Transmitters

Not all the techniques proposed have, of course, been based on radio techniques, but they are the most important ones for two main reasons: their level of development and maturity on the one hand and their ability to "cross" or to "get around" obstacles such as walls, furniture or people on the other hand. Optical based techniques, like laser based distance measurements or vision based (camera) scene analysis systems present some real advantages in terms of measurement accuracy (a few millimetres for the former) or orientation determination (very useful for any guidance system, available for the latter). Unfortunately, the foreseen use of positioning devices being mainly dedicated to pedestrians in urban environments, optical obstacles are numerous. These latter techniques are then considered as potential hybridisation candidates. Many types of sensors have also been studied for positioning, such as infrared or ultrasound. Once again, although accuracy can reach centimetre values, the environmental constraints are not compatible with the ubiquitous systems being sought. Another category is, of course, inertial systems which could be a valuable alternative to radio systems: time and distance associated position drifts are not yet sufficiently mastered and the given positioning is relative , which means the need for "something else" in order to provide the user with an absolute location. The object of this section is to focus on radio based approaches

Hybridation MEMS/UWB pour la navigation pédestre intra-muros

Facing the expansion of geolocation needs, illustrated by the GALILEO European project, the growth of Location Based Services (LBS) and the need to identify the location of emergency mobile phone calls in Europe (standard E112), the research on localization techniques is booming. This thesis focuses on indoor pedestrian navigation and investigates a localization solution based on micro-electromechanical systems (MEMS) and ultra-wideband waves (UWB). MEMS based localization estimates the current location from a previously determined position using on-board low-cost inertial embedded sensors. Unfortunately, the performances of these autonomous systems are affected by large errors (typical of these sensors). In fact standalone solutions drift rapidly with time. Impulse-Radio UWB (IR-UWB) Times Of Arrival (TOA) are often used for localization purposes. This network based technology uses sensor networks, mainly attached to the infrastructure of the building to estimate the location of the transmitter with decimetre accuracy in ideal scenarii. However the indoor environment is hostile for radio propagation. Full of artificial obstacles, electromagnetic waves are disturbed and radiolocation performances are reduced. Construction materials also affect the magnetic field used to estimate the pedestrian's walking direction. In this context, the hybridization of these two complementary and uncorrelated technologies is promising. The study of the movement pattern of a pedestrian walking indoors induces two main outcomes on localization techniques. Firstly, random pedestrian movements complicate MEMS signal processing. Secondly, when the transmitter is worn by the user, for example around the neck, IR-UWB that propagates through the human body can hardly contribute to the localization. Optimal data fusion filters that hybridize a large set of observations : Angles Of Arrival (AOA), Time Differences Of Arrival (TDOA), accelerations, angular velocities and magnetic field measurements are presented. The coupling of UWB and MEMS data relies on an Extended Kalman Filter (EKF) complemented with specific procedures. Loose integration and tight integration are considered. Outlier detection processes within the radio data enrich the EKF. The most remarkable process is based on the RANSAC paradigm and employs the physical constraints of the pedestrian's walk described by biomechanics. In some cases, it enables the processing of reflected radio signals. A user equipped with a MEMS module and an UWB transceiver walked in the premises of the EPFL, following nine independent paths, for a total length of 380 m. The benefit of the MEMS/UWB hybridization filters are evaluated based on this experiment. The tight integration outperforms the loose coupling and enables indoor pedestrian localization with a one metre accuracy

Augmented Reality

Augmented Reality (AR) is a natural development from virtual reality (VR), which was developed several decades earlier. AR complements VR in many ways. Due to the advantages of the user being able to see both the real and virtual objects simultaneously, AR is far more intuitive, but it's not completely detached from human factors and other restrictions. AR doesn't consume as much time and effort in the applications because it's not required to construct the entire virtual scene and the environment. In this book, several new and emerging application areas of AR are presented and divided into three sections. The first section contains applications in outdoor and mobile AR, such as construction, restoration, security and surveillance. The second section deals with AR in medical, biological, and human bodies. The third and final section contains a number of new and useful applications in daily living and learning

Hybrid Visual-Inertial/Magnetic 3D Pose Estimation for Tracking Poorly-Textured/Textureless Symmetrical Objects

The focus of this research is mainly to develop a visual 3D pose estimation that can be used for many purposes including but not limited to autonomous visual inspection support system. The work overcomes the fundamental problem of region-based pose estimation in tracking poorly-textured/textureless symmetrical objects due to non-unique projection shape given numerous different poses. The work improved the existing state-of-the-art region-based pose estimation, known as Pixel-Wise Posterior 3D Pose estimation (PWP3D), by incorporating with inertial/magnetic orientation estimate. For this purpose, an inertial/magnetic orientation estimate expressed as a full optimisation problem is proposed beforehand. The proposed method, referred to NAG-AHRS, aims to deal better with the non-Gaussian noise and the non-linear model. The NAG-AHRS is then analysed by comparing its output to the motion capture system, as well as benchmarked to five state-of-the-art inertial/magnetic orientation estimates. The experiments show NAG-AHRS outperformed other benchmarking algorithms. Furthermore, NAG-AHRS facilitates the integration to visual-only pose estimation and to develop hybrid visual-inertial/magnetic pose estimation. In contrast with common visual-inertial integration method that has been dominated by Kalman filtering framework, the proposed method integrates visual and inertial/magnetic as a single optimisation problem. The selected optimisation method is Nesterov’s Accelerated Gradient (NAG) descent, hence the proposed method is referred to as PWP3Di-NAG. The developed PWP3Di-NAG algorithm is then validated by comparing its output to the reference pose provided by Aruco marker and at the same time, it is also benchmarked to the original PWP3D algorithm. The validation demonstrated some significant performances improvements. Moreover, integrating visual-inertial as a single optimisation problem requires to transform inertial/magnetic measurements into the object reference frame. The required transformation induces an initialisation stage to accurately estimate the initial pose of the object. A novel framework for serving this purpose that combines region-based and edge-based pose estimation in a particle filtering framework is also proposed. The validation shows that the proposed framework be able to estimate the pose of an object with low pose estimation errors

Benefits from a multi-receiver architecture for GNSS precise positioning

Precise positioning with a stand-alone GPS receiver or using differential corrections is known to be strongly degraded in an urban or sub-urban environment due to frequent signal masking, strong multipath effect, frequent cycle slips on carrier phase, etc. The objective of this Ph.D. thesis is to explore the possibility of achieving precise positioning with a low-cost architecture using multiple installed low-cost single-frequency receivers with known geometry whose one of them is RTK positioned w.r.t an external reference receiver. This setup is thought to enable vehicle attitude determination and RTK performance amelioration. In this thesis, we firstly proposed a method that includes an array of receivers with known geometry to enhance the performance of the RTK in different environments. Taking advantage of the attitude information and the known geometry of the installed array of receivers, the improvement of some internal steps of RTK w.r.t an external reference receiver can be achieved. The navigation module to be implemented in this work is an Extended Kalman Filter (EKF). The performance of a proposed two-receiver navigation architecture is then studied to quantify the improvements brought by the measurement redundancy. This concept is firstly tested on a simulator in order to validate the proposed algorithm and to give a reference result of our multi-receiver system’s performance. The pseudorange measurements and carrier phase measurements mathematical models are implemented in a realistic simulator. Different scenarios are conducted, including varying the distance between the 2 antennas of the receiver array, the satellite constellation geometry, and the amplitude of the noise measurement, in order to determine the influence of the use of an array of receivers. The simulation results show that our multi-receiver RTK system w.r.t an external reference receiver is more robust to noise and degraded satellite geometry, in terms of ambiguity fixing rate, and gets a better position accuracy under the same conditions when compared with the single receiver system. Additionally, our method achieves a relatively accurate estimation of the attitude of the vehicle which provides additional information beyond the positioning. In order to optimize our processing, the correlation of the measurement errors affecting observations taken by our array of receivers has been determined. Then, the performance of our real-time single frequency cycle-slip detection and repair algorithm has been assessed. These two investigations yielded important information so as to tune our Kalman Filter. The results obtained from the simulation made us eager to use actual data to verify and improve our multi-receiver RTK and attitude system. Tests based on real data collected around Toulouse, France, are used to test the performance of the whole methodology, where different scenarios are conducted, including varying the distance between the 2 antennas of the receiver array as well as the environmental conditions (open sky, suburban, and constrained urban environments). The thesis also tried to take advantage of a dual GNSS constellation, GPS and Galileo, to further strengthen the position solution and the reliable use of carrier phase measurements. The results show that our multi-receiver RTK system is more robust to degraded GNSS environments. Our experiments correlate favorably with our previous simulation results and further support the idea of using an array of receivers with known geometry to improve the RTK performance