Exploiting the spatio-temporal channel properties of multiple antenna systems

The spatio-temporal channel properties of multiple antenna systems are exploited to obtain new approaches to localization and channel prediction. It is shown that a mobile station can be localized in multipath environments under the explicit consideration of scatterers. Thus, unlike conventional localization systems, the scatterers are used as an aid in localization. Moreover, it is shown that channel prediction in multiple antenna systems can be performed using linear prediction filters. This result is used to propose optimal and computationally inexpensive suboptimal channel predictors

FPGA-based High Performance Diagnostics For Fusion

High performance diagnostics are an important aspect of fusion research. Increasing shot-lengths paired with the requirement for higher accuracy and speed make it mandatory to employ new technology to cope with the increasing demands on digitization and data handling. Field programmable gate arrays (FPGAs) are well known in high performance applications. Their ability to handle multiple fast data streams whilst remaining programmable make them an ideal tool for diagnostic development. Both the improvement of old and the design of new diagnostics can benefit from FPGA-technology and increase the amount of accessible physics significantly. In this work the developments on two FPGA-based diagnostics are presented. In the first part a new open-hardware low-cost FPGA-based digitizer is presented for the MAST-Upgrade (MAST-U) integral electron density interferometer. The system is shown to have an optically limited phase accuracy and a detection bandwidth of over 3.5 MHz. Data is acquired continuously at 20 MS/s and streamed to an acquisition PC via optical fiber. By employing a dual-FPGA approach real-time processing of the density signal can be achieved despite severly limited resources, thus providing a control signal for the MAST-U plasma control system system with less than 8 μs latency. Due to MAST-U being still inoperable, in-situ testing has been conducted on the ASDEX Upgrade, where fast wave physics up to 3.5 MHz could first be observed. The second part presents developments to the Synthetic Aperture Microwave Imaging (SAMI) diagnostic. In addition to improving the utilization of long shot-lengths and enabling dual-polarized acquisition the system has been enhanced to continuously acquire active probing profiles for 2D Doppler back-scattering (DBS), a technique recently developed using SAMI. The aim is to measure pitch angle profiles to derive the edge current density. SAMI has been transferred to the NSTX-Upgrade and integrated into the experiment’s infrastructure, where it has been acquiring data since May 2016. As part of this move an investigation into near-field effects on SAMI’s image reconstruction algorithms was conducted

Radio Communications

In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modified our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the field of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks

A Review of Indoor Millimeter Wave Device-based Localization and Device-free Sensing Technologies and Applications

The commercial availability of low-cost millimeter wave (mmWave) communication and radar devices is starting to improve the penetration of such technologies in consumer markets, paving the way for large-scale and dense deployments in fifth-generation (5G)-and-beyond as well as 6G networks. At the same time, pervasive mmWave access will enable device localization and device-free sensing with unprecedented accuracy, especially with respect to sub-6 GHz commercial-grade devices. This paper surveys the state of the art in device-based localization and device-free sensing using mmWave communication and radar devices, with a focus on indoor deployments. We first overview key concepts about mmWave signal propagation and system design. Then, we provide a detailed account of approaches and algorithms for localization and sensing enabled by mmWaves. We consider several dimensions in our analysis, including the main objectives, techniques, and performance of each work, whether each research reached some degree of implementation, and which hardware platforms were used for this purpose. We conclude by discussing that better algorithms for consumer-grade devices, data fusion methods for dense deployments, as well as an educated application of machine learning methods are promising, relevant and timely research directions.Comment: 43 pages, 13 figures. Accepted in IEEE Communications Surveys & Tutorials (IEEE COMST

Sonar systems for object recognition

The deep sea exploration and exploitation is one of the biggest challenges of the next century. Military, oil & gas, o shore wind farming, underwater mining, oceanography are some of the actors interested in this eld. The engineering and technical challenges to perform any tasks underwater are great but the most crucial element in any underwater systems has to be the sensors. In air numerous sensor systems have been developed: optic cameras, laser scanner or radar systems. Unfortunately electro magnetic waves propagate poorly in water, therefore acoustic sensors are a much preferred tool then optical ones. This thesis is dedicated to the study of the present and the future of acoustic sensors for detection, identi cation or survey. We will explore several sonar con gurations and designs and their corresponding models for target scattering. We will show that object echoes can contain essential information concerning its structure and/or composition

System design of the MeerKAT L - band 3D radar for monitoring near earth objects

This thesis investigates the current knowledge of small space debris (diameter less than 10 cm) and potentially hazardous asteroids (PHA) by the use of radar systems. It clearly identifies the challenges involved in detecting and tracking of small space debris and PHAs. The most significant challenges include: difficulty in tracking small space debris due to orbital instability and reduced radar cross-section (RCS), errors in some existing data sets, the lack of dedicated or contributing instruments in the Southern Hemisphere, and the large cost involved in building a high-performance radar for this purpose. This thesis investigates the cooperative use of the KAT-7 (7 antennas) and MeerKAT (64 antennas) radio telescope receivers in a radar system to improve monitoring of small debris and PHAs was investigated using theory and simulations, as a cost-effective solution. Parameters for a low cost and high-performance radar were chosen, based on the receiver digital back-end. Data from such radars will be used to add to existing catalogues thereby creating a constantly updated database of near Earth objects and bridging the data gap that is currently being filled by mathematical models. Based on literature and system requirements, quasi-monostatic, bistatic, multistatic, single input multiple output (SIMO) radar configurations were proposed for radio telescope arrays in detecting, tracking and imaging small space debris in the low Earth orbit (LEO) and PHAs. The maximum dwell time possible for the radar geometry was found to be 30 seconds, with coherent integration limitations of 2 ms and 121 ms for accelerating and non-accelerating targets, respectively. The multistatic and SIMO radar configurations showed sufficient detection (SNR 13 dB) for small debris and quasi-monostatic configuration for PHAs. Radar detection, tracking and imaging (ISAR) simulations were compared to theory and ambiguities in range and Doppler were compensated for. The main contribution made by this work is a system design for a high performance, cost effective 3D radar that uses the KAT-7 and MeerKAT radio telescope receivers in a commensal manner. Comparing theory and simulations, the SNR improvement, dwell time increase, tracking and imaging capabilities, for small debris and PHAs compared to existing assets, was illustrated. Since the MeerKAT radio telescope is a precursor for the SKA Africa, extrapolating the capabilities of the MeerKAT radar to the SKA radar implies that it would be the most sensitive and high performing contributor to space situational awareness, upon its completion. From this feasibility study, the MeerKAT 3D distributed radar will be able to detect debris of diameter less than 10 cm at altitudes between 700 km to 900 km, and PHAs, with a range resolution of 15 m, a minimum SNR of 14 dB for 152 pulses for a coherent integration time of 2.02 ms. The target range (derived from the two way delay), velocity (from Doppler frequency) and direction will be measured within an accuracy of: 2.116 m, 15.519 m/s, 0.083° (single antenna), respectively. The range, velocity accuracies and SNR affect orbit prediction accuracy by 0.021 minutes for orbit period and 0.0057° for orbit inclination. The multistatic radar was found to be the most suitable and computationally efficient configuration compared to the bistatic and SIMO configurations, and beamforming should be implemented as required by specific target geometry

Sensorisation of a novel biologically inspired flexible needle

Percutaneous interventions are commonly performed during minimally invasive brain surgery, where a straight rigid instrument is inserted through a small incision to access a deep lesion in the brain. Puncturing a vessel during this procedure can be a life-threatening complication. Embedding a forward-looking sensor in a rigid needle has been proposed to tackle this problem; however, using a rigid needle, the procedure needs to be interrupted if a vessel is detected. Steerable needle technology could be used to avoid obstacles, such as blood vessels, due to its ability to follow curvilinear paths, but research to date was lacking in this respect. This thesis aims to investigate the deployment of forward-looking sensors for vessel detection in a steerable needle. The needle itself is based on a bioinspired programmable bevel-tip needle (PBN), a multi-segment design featuring four hollow working channels. In this thesis, laser Doppler flowmetry (LDF) is initially characterised to ensure that the sensor fulfils the minimum requirements for it to be used in conjunction with the needle. Subsequently, vessel reconstruction algorithms are proposed. To determine the axial and off-axis position of the vessel with respect to the probe, successive measurements of the LDF sensor are used. Ideally, full knowledge of the vessel orientation is required to execute an avoidance strategy. Using two LDF probes and a novel signal processing method described in this thesis, the predicted possible vessel orientations can be reduced to four, a setup which is explored here to demonstrate viable obstacle detection with only partial sensor information. Relative measurements from four LDF sensors are also explored to classify possible vessel orientations in full and without ambiguity, but under the assumption that the vessel is perpendicular to the needle insertion axis. Experimental results on a synthetic grey matter phantom are presented, which confirm these findings. To release the perpendicularity assumption, the thesis concludes with the description of a machine learning technique based on a Long Short-term memory network, which enables a vessel's spatial position, cross-sectional diameter and full pose to be predicted with sub-millimetre accuracy. Simulated and in-vitro examinations of vessel detection with this approach are used to demonstrate effective predictive ability. Collectively, these results demonstrate that the proposed steerable needle sensorisation is viable and could lead to improved safety during robotic assisted needle steering interventions.Open Acces