New Approach of Indoor and Outdoor Localization Systems

Accurate determination of the mobile position constitutes the basis of many new applications. This book provides a detailed account of wireless systems for positioning, signal processing, radio localization techniques (Time Difference Of Arrival), performances evaluation, and localization applications. The first section is dedicated to Satellite systems for positioning like GPS, GNSS. The second section addresses the localization applications using the wireless sensor networks. Some techniques are introduced for localization systems, especially for indoor positioning, such as Ultra Wide Band (UWB), WIFI. The last section is dedicated to Coupled GPS and other sensors. Some results of simulations, implementation and tests are given to help readers grasp the presented techniques. This is an ideal book for students, PhD students, academics and engineers in the field of Communication, localization & Signal Processing, especially in indoor and outdoor localization domains

Towards a Model Based Sensor Measurement Variance Input for Extended Kalman Filter State Estimation

In this paper, we present an alternate method for the generation and implementation of the sensor measurement variance used in an Extended Kalman Filter (EKF). Furthermore, it demonstrates the limitations of a conventional EKF implementation and postulates an alternate form for representing the sensor measurement variance by extending and improving the characterisation methodology presented in the previous work. As presented in earlier work, the use of surveying grade optical measurement instruments allows for a more effective characterisation of Ultra-Wide Band (UWB) localisation sensors; however, in cluttered environments, the sensor measurement variance will change, making this method not robust. To compensate for the noisier readings, an EKF using a model based sensor measurement variance was developed. This approach allows for a more accurate representation of the sensor measurement variance and leads to a more robust state estimation system. Simulations were run using synthetic data in order to test the effectiveness of the EKF against the originally developed EKF; next, the new EKF was compared to the original EKF using real world data. The new EKF was shown to function much more stably and consistently in less ideal environments for UWB deployment than the previous version

Analysis and Accuracy Improvement of UWB-TDoA-Based Indoor Positioning System

Positioning systems are used in a wide range of applications which require determining the position of an object in space, such as locating and tracking assets, people and goods; assisting navigation systems; and mapping. Indoor Positioning Systems (IPSs) are used where satellite and other outdoor positioning technologies lack precision or fail. Ultra-WideBand (UWB) technology is especially suitable for an IPS, as it operates under high data transfer rates over short distances and at low power densities, although signals tend to be disrupted by various objects. This paper presents a comprehensive study of the precision, failure, and accuracy of 2D IPSs based on UWB technology and a pseudo-range multilateration algorithm using Time Difference of Arrival (TDoA) signals. As a case study, the positioning of a 4×4m2 area, four anchors (transceivers), and one tag (receiver) are considered using bitcraze’s Loco Positioning System. A Cramér–Rao Lower Bound analysis identifies the convex hull of the anchors as the region with highest precision, taking into account the anisotropic radiation pattern of the anchors’ antennas as opposed to ideal signal distributions, while bifurcation envelopes containing the anchors are defined to bound the regions in which the IPS is predicted to fail. This allows the formulation of a so-called flyable area, defined as the intersection between the convex hull and the region outside the bifurcation envelopes. Finally, the static bias is measured after applying a built-in Extended Kalman Filter (EKF) and mapped using a Radial Basis Function Network (RBFN). A debiasing filter is then developed to improve the accuracy. Findings and developments are experimentally validated, with the IPS observed to fail near the anchors, precision around ±3cm, and accuracy improved by about 15cm for static and 5cm for dynamic measurements, on average

Communication-based UAV Swarm Missions

Unmanned aerial vehicles have developed rapidly in recent years due to technological advances. UAV technology can be applied to a wide range of applications in surveillance, rescue, agriculture and transport. The problems that can exist in these areas can be mitigated by combining clusters of drones with several technologies. For example, when a swarm of drones is under attack, it may not be able to obtain the position feedback provided by the Global Positioning System (GPS). This poses a new challenge for the UAV swarm to fulfill a specific mission. This thesis intends to use as few sensors as possible on the UAVs and to design the smallest possible information transfer between the UAVs to maintain the shape of the UAV formation in flight and to follow a predetermined trajectory. This thesis presents Extended Kalman Filter methods to navigate autonomously in a GPS-denied environment. The UAV formation control and distributed communication methods are also discussed and given in detail

Precise Onboard Aircraft Cabin Localization using UWB and ML

Precise indoor positioning systems (IPSs) are key to perform a set of tasks more efficiently during aircraft production, operation and maintenance. For instance, IPSs can overcome the tedious task of configuring (wireless) sensor nodes in an aircraft cabin. Although various solutions based on technologies of established consumer goods, e.g., Bluetooth or WiFi, have been proposed and tested, the published accuracy results fail to make these technologies relevant for practical use cases. This stems from the challenging environments for positioning, especially in aircraft cabins, which is mainly due to the geometries, many obstacles, and highly reflective materials. To address these issues, we propose to evaluate in this work an Ultra-Wideband (UWB)-based IPS via a measurement campaign performed in a real aircraft cabin. We first illustrate the difficulties that an IPS faces in an aircraft cabin, by studying the signal propagation effects which were measured. We then investigate the ranging and localization accuracies of our IPS. Finally, we also introduce various methods based on machine learning (ML) for correcting the ranging measurements and demonstrate that we are able to localize a node with respect to an aircraft seat with a measured likelihood of 97%

Map matching by using inertial sensors: literature review

This literature review aims to clarify what is known about map matching by using inertial sensors and what are the requirements for map matching, inertial sensors, placement and possible complementary position technology. The target is to develop a wearable location system that can position itself within a complex construction environment automatically with the aid of an accurate building model. The wearable location system should work on a tablet computer which is running an augmented reality (AR) solution and is capable of track and visualize 3D-CAD models in real environment. The wearable location system is needed to support the system in initialization of the accurate camera pose calculation and automatically finding the right location in the 3D-CAD model. One type of sensor which does seem applicable to people tracking is inertial measurement unit (IMU). The IMU sensors in aerospace applications, based on laser based gyroscopes, are big but provide a very accurate position estimation with a limited drift. Small and light units such as those based on Micro-Electro-Mechanical (MEMS) sensors are becoming very popular, but they have a significant bias and therefore suffer from large drifts and require method for calibration like map matching. The system requires very little fixed infrastructure, the monetary cost is proportional to the number of users, rather than to the coverage area as is the case for traditional absolute indoor location systems.Siirretty Doriast

5G-PPP Technology Board:Delivery of 5G Services Indoors - the wireless wire challenge and solutions

The 5G Public Private Partnership (5G PPP) has focused its research and innovation activities mainly on outdoor use cases and supporting the user and its applications while on the move. However, many use cases inherently apply in indoor environments whereas their requirements are not always properly reflected by the requirements eminent for outdoor applications. The best example for indoor applications can be found is the Industry 4.0 vertical, in which most described use cases are occurring in a manufacturing hall. Other environments exhibit similar characteristics such as commercial spaces in offices, shopping malls and commercial buildings. We can find further similar environments in the media & entertainment sector, culture sector with museums and the transportation sector with metro tunnels. Finally in the residential space we can observe a strong trend for wireless connectivity of appliances and devices in the home. Some of these spaces are exhibiting very high requirements among others in terms of device density, high-accuracy localisation, reliability, latency, time sensitivity, coverage and service continuity. The delivery of 5G services to these spaces has to consider the specificities of the indoor environments, in which the radio propagation characteristics are different and in the case of deep indoor scenarios, external radio signals cannot penetrate building construction materials. Furthermore, these spaces are usually “polluted” by existing wireless technologies, causing a multitude of interreference issues with 5G radio technologies. Nevertheless, there exist cases in which the co-existence of 5G new radio and other radio technologies may be sensible, such as for offloading local traffic. In any case the deployment of networks indoors is advised to consider and be planned along existing infrastructure, like powerlines and available shafts for other utilities. Finally indoor environments expose administrative cross-domain issues, and in some cases so called non-public networks, foreseen by 3GPP, could be an attractive deployment model for the owner/tenant of a private space and for the mobile network operators serving the area. Technology-wise there exist a number of solutions for indoor RAN deployment, ranging from small cell architectures, optical wireless/visual light communication, and THz communication utilising reconfigurable intelligent surfaces. For service delivery the concept of multi-access edge computing is well tailored to host virtual network functions needed in the indoor environment, including but not limited to functions supporting localisation, security, load balancing, video optimisation and multi-source streaming. Measurements of key performance indicators in indoor environments indicate that with proper planning and consideration of the environment characteristics, available solutions can deliver on the expectations. Measurements have been conducted regarding throughput and reliability in the mmWave and optical wireless communication cases, electric and magnetic field measurements, round trip latency measurements, as well as high-accuracy positioning in laboratory environment. Overall, the results so far are encouraging and indicate that 5G and beyond networks must advance further in order to meet the demands of future emerging intelligent automation systems in the next 10 years. Highly advanced industrial environments present challenges for 5G specifications, spanning congestion, interference, security and safety concerns, high power consumption, restricted propagation and poor location accuracy within the radio and core backbone communication networks for the massive IoT use cases, especially inside buildings. 6G and beyond 5G deployments for industrial networks will be increasingly denser, heterogeneous and dynamic, posing stricter performance requirements on the network. The large volume of data generated by future connected devices will put a strain on networks. It is therefore fundamental to discriminate the value of information to maximize the utility for the end users with limited network resources

Distance-based sensor node localization by using ultrasound, RSSI and ultra-wideband - A comparision between the techniques

Wireless sensor networks (WSNs) have become one of the most important topics in wireless communication during the last decade. In a wireless sensor system, sensors are spread over a region to build a sensor network and the sensors in a region co-operate to each other to sense, process, filter and routing. Sensor Positioning is a fundamental and crucial issue for sensor network operation and management. WSNs have so many applications in different areas such as health-care, monitoring and control, rescuing and military; they all depend on nodes being able to accurately determine their locations. This master’s thesis is focused on distance-based sensor node localization techniques; Received signal strength indicator, ultrasound and ultra-wideband. Characteristics and factors which affect these distance estimation techniques are analyzed theoretically and through simulation the quality of these techniques are compared in different scenarios. MDS, a centralized algorithm is used for solving the coordinates. It is a set of data analysis techniques that display the structure of distance-like data as a geometrical picture. Centralized and distributed implementations of MDS are also discussed. All simulations and computations in this thesis are done in Matlab. Virtual WSN is simulated on Sensorviz. Sensorviz is a simulation and visualization tool written by Andreas Savvides.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format