MOSAIC: Simultaneous Localization and Environment Mapping using mmWave without a-priori Knowledge

Simultaneous Localization and environment mapping (SLAM) is the core to robotic mapping and navigation as it constructs simultaneously the unknown environment and localizes the agent within. However, in millimeter wave (mmWave) research, SLAM is still at its infancy. In this paper, we introduce MOSAIC a new approach for SLAM in indoor environment by exploiting the map-based channel model. More precisely, we perform localization and environment inference through obstacle detection and dimensioning. The concept of Virtual Anchor Nodes (VANs), known in literature as the mirrors of the real anchors with respect to the obstacles in the environment, is firstly introduced. Then, based on these VANs, the obstacles positionsand dimensions are estimated by detecting the zone of pathsobstruction, points of reflection and obstacle vertices estimation.Cramer-Rao Lower Bounds (CRLB) are then derived to find the optimal number of anchor nodes and measurements points that improve the localization and mapping accuracy. Simulation results have shown high localization accuracy and obstacle detection in different environments using mmWave technology

Wireless Positioning and Tracking for Internet of Things in GPS-denied Environments

Wireless positioning and tracking have long been a critical technology for various applications such as indoor/outdoor navigation, surveillance, tracking of assets and employees, and guided tours, among others. Proliferation of Internet of Things (IoT) devices, the evolution of smart cities, and vulnerabilities of traditional localization technologies to cyber-attacks such as jamming and spoofing of GPS necessitate development of novel radio frequency (RF) localization and tracking technologies that are accurate, energy-efficient, robust, scalable, non-invasive and secure. The main challenges that are considered in this research work are obtaining fundamental limits of localization accuracy using received signal strength (RSS) information with directional antennas, and use of burst and intermittent measurements for localization. In this dissertation, we consider various RSS-based techniques that rely on existing wireless infrastructures to obtain location information of corresponding IoT devices. In the first approach, we present a detailed study on localization accuracy of UHF RF IDentification (RFID) systems considering realistic radiation pattern of directional antennas. Radiation patterns of antennas and antenna arrays may significantly affect RSS in wireless networks. The sensitivity of tag antennas and receiver antennas play a crucial role. In this research, we obtain the fundamental limits of localization accuracy considering radiation patterns and sensitivity of the antennas by deriving Cramer-Rao Lower Bounds (CRLBs) using estimation theory techniques. In the second approach, we consider a millimeter Wave (mmWave) system with linear antenna array using beamforming radiation patterns to localize user equipment in an indoor environment. In the third approach, we introduce a tracking and occupancy monitoring system that uses ambient, bursty, and intermittent WiFi probe requests radiated from mobile devices. Burst and intermittent signals are prominent characteristics of IoT devices; using these features, we propose a tracking technique that uses interacting multiple models (IMM) with Kalman filtering. Finally, we tackle the problem of indoor UAV navigation to a wireless source using its Rayleigh fading RSS measurements. We propose a UAV navigation technique based on Q-learning that is a model-free reinforcement learning technique to tackle the variation in the RSS caused by Rayleigh fading

Lightweight indoor localization for 60-GHz millimeter wave systems

In this paper, we target single-anchor localization schemes for millimeter wave (MMW) systems. The schemes are designed to be lightweight, so that even computationally-constrained devices can support them. We identify the main propagation properties of MMW signals that have an impact on localization and design three algorithms that exploit these, namely a triangulation-validation procedure, an angle difference-of-arrival approach, and a scheme based on location fingerprinting. We evaluate the algorithms by means of simulations, and draw conclusions on their robustness. We then validate our results via measurements involving commercial pre- standard 60- GHz MMW hardware. Our experiments confirm that, by relying only on a single anchor and without requiring complex signal processing at the receiver, the algorithms can localize a node with high probability, and in many cases with sub-meter accuracy. We conclude by discussing how these algorithms complement each other in terms of robustness and localization success probability

Protocolos multibanda para descoberta de vizinhança em redes ad hoc de ondas milimétricas

Propagation at millimeter waves band, i.e. up from 30 GHz, is very susceptible to path loss attenuation, which can be mitigated using highly directional antennas. Hence, the usage of millimeter waves band in ad hoc networks increases the complexity of neighbor discovery since the knowledge of neighbors’ physical location becomes essential to proceed with communication. To face these challenges, multiband protocols have been proposed, which uses an omnidirectional control channel in a different band from millimeter waves data channel. Due to unstable characteristics of millimeter waves channel, the control channel is used to transmit information concerning neighbor discovery. The two protocols proposed in this work rely on this feature and aim to build a global knowledge about nodes’ location as well as to maintain it in the case of nodes mobility or if some obstacle arises. Both protocols are compared with another protocol found in the literature in terms of delay on the neighbor discoveryA propagação na banda de ondas milimétricas, ou seja, a partir de 30 GHz, é altamente suscetível à atenuação por perda de percurso. Esta acentuada atenuação é mitigada pelo uso de antenas altamente direcionais. Assim, o uso da banda de ondas milimétricas em redes ad hoc aumenta a complexidade na descoberta de vizinhos, pois se torna essencial obter a localização física dos vizinhos para proceder com a comunicação. Para lidar com esse desafio, protocolos multibanda foram propostos na literatura, os quais fazem uso de um canal de controle omnidirecional em uma banda diferente do canal de dados em ondas milimétricas. Devido às instabilidades deste último canal, o canal de controle é usado para transmissão das informações pertinentes à realização de busca dos vizinhos. Os dois protocolos propostos neste trabalho fazem uso dessa funcionalidade e visam construir o conhecimento do posicionamento de todos os nós da rede, assim como manter esta informação em caso de mudanças de posicionamento ou surgimento de obstáculos. Ambos os protocolos são comparados com um outro protocolo da literatura em termos da latência na descoberta de vizinhança

Wireless indoor localisation within the 5G internet of radio light

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonNumerous applications can be enhanced by accurate and efficient indoor localisation using wireless sensor networks, however trade-offs often exist between these two parameters. In this thesis, realworld and simulation data is used to examine the hybrid millimeter wave and Visible Light Communications (VLC) architecture of the 5G Internet of Radio Light (IoRL) Horizon 2020 project. Consequently, relevant localisation challenges within Visible Light Positioning (VLP) and asynchronous sampling networks are identified, and more accurate and efficient solutions are developed. Currently, VLP relies strongly on the assumed Lambertian properties of light sources. However, in practice, not all lights are Lambertian. To support the widespread deployment of VLC technology in numerous environments, measurements from non-Lambertian sources are analysed to provide new insights into the limitations of existing VLP techniques. Subsequently, a novel VLP calibration technique is proposed, and results indicate a 59% accuracy improvement against existing methods. This solution enables high accuracy centimetre level VLP to be achieved with non- Lambertian sources. Asynchronous sampling of range-based measurements is known to impact localisation performance negatively. Various Asynchronous Sampling Localisation Techniques (ASLT) exist to mitigate these effects. While effective at improving positioning performance, the exact suitability of such solutions is not evident due to their additional processes, subsequent complexity, and increased costs. As such, extensive simulations are conducted to study the effectiveness of ASLT under variable sampling latencies, sensor measurement noise, and target trajectories. Findings highlight the computational demand of existing ASLT and motivate the development of a novel solution. The proposed Kalman Extrapolated Least Squares (KELS) method achieves optimal localisation performance with a significant energy reduction of over 50% when compared to current leading ASLT. The work in this thesis demonstrates both the capability for high performance VLP from non- Lambertian sources as well as the potential for energy efficient localisation for sequentially sampled range measurements.Horizon 202