Metrics to evaluate compressions algorithms for RAW SAR data

Modern synthetic aperture radar (SAR) systems have size, weight, power and cost (SWAP-C) limitations since platforms are becoming smaller, while SAR operating modes are becoming more complex. Due to the computational complexity of the SAR processing required for modern SAR systems, performing the processing on board the platform is not a feasible option. Thus, SAR systems are producing an ever-increasing volume of data that needs to be transmitted to a ground station for processing. Compression algorithms are utilised to reduce the data volume of the raw data. However, these algorithms can cause degradation and losses that may degrade the effectiveness of the SAR mission. This study addresses the lack of standardised quantitative performance metrics to objectively quantify the performance of SAR data-compression algorithms. Therefore, metrics were established in two different domains, namely the data domain and the image domain. The data-domain metrics are used to determine the performance of the quantisation and the associated losses or errors it induces in the raw data samples. The image-domain metrics evaluate the quality of the SAR image after SAR processing has been performed. In this study three well-known SAR compression algorithms were implemented and applied to three real SAR data sets that were obtained from a prototype airborne SAR system. The performance of these algorithms were evaluated using the proposed metrics. Important metrics in the data domain were found to be the compression ratio, the entropy, statistical parameters like the skewness and kurtosis to measure the deviation from the original distributions of the uncompressed data, and the dynamic range. The data histograms are an important visual representation of the effects of the compression algorithm on the data. An important error measure in the data domain is the signal-to-quantisation-noise ratio (SQNR), and the phase error for applications where phase information is required to produce the output. Important metrics in the image domain include the dynamic range, the impulse response function, the image contrast, as well as the error measure, signal-to-distortion-noise ratio (SDNR). The metrics suggested that all three algorithms performed well and are thus well suited for the compression of raw SAR data. The fast Fourier transform block adaptive quantiser (FFT-BAQ) algorithm had the overall best performance, but the analysis of the computational complexity of its compression steps, indicated that it is has the highest level of complexity compared to the other two algorithms. Since different levels of degradation are acceptable for different SAR applications, a trade-off can be made between the data reduction and the degradation caused by the algorithm. Due to SWAP-C limitations, there also remains a trade-off between the performance and the computational complexity of the compression algorithm.Dissertation (MEng)--University of Pretoria, 2019.Electrical, Electronic and Computer EngineeringMEngUnrestricte

Metrics to evaluate compressions algorithms for RAW SAR data

Modern synthetic aperture radar (SAR) systems have size, weight, power and cost (SWAP-C) limitations since platforms are becoming smaller, while SAR operating modes are becoming more complex. Due to the computational complexity of the SAR processing required for modern SAR systems, performing the processing on board the platform is not a feasible option. Thus, SAR systems are producing an ever-increasing volume of data that needs to be transmitted to a ground station for processing. Compression algorithms are utilised to reduce the data volume of the raw data. However, these algorithms can cause degradation and losses that may degrade the effectiveness of the SAR mission. This study addresses the lack of standardised quantitative performance metrics to objectively quantify the performance of SAR data-compression algorithms. Therefore, metrics were established in two different domains, namely the data domain and the image domain. The data-domain metrics are used to determine the performance of the quantisation and the associated losses or errors it induces in the raw data samples. The image-domain metrics evaluate the quality of the SAR image after SAR processing has been performed. In this study three well-known SAR compression algorithms were implemented and applied to three real SAR data sets that were obtained from a prototype airborne SAR system. The performance of these algorithms were evaluated using the proposed metrics. Important metrics in the data domain were found to be the compression ratio, the entropy, statistical parameters like the skewness and kurtosis to measure the deviation from the original distributions of the uncompressed data, and the dynamic range. The data histograms are an important visual representation of the effects of the compression algorithm on the data. An important error measure in the data domain is the signal-to-quantisation-noise ratio (SQNR), and the phase error for applications where phase information is required to produce the output. Important metrics in the image domain include the dynamic range, the impulse response function, the image contrast, as well as the error measure, signal-to-distortion-noise ratio (SDNR). The metrics suggested that all three algorithms performed well and are thus well suited for the compression of raw SAR data. The fast Fourier transform block adaptive quantiser (FFT-BAQ) algorithm had the overall best performance, but the analysis of the computational complexity of its compression steps, indicated that it is has the highest level of complexity compared to the other two algorithms. Since different levels of degradation are acceptable for different SAR applications, a trade-off can be made between the data reduction and the degradation caused by the algorithm. Due to SWAP-C limitations, there also remains a trade-off between the performance and the computational complexity of the compression algorithm.Dissertation (MEng)--University of Pretoria, 2019.TM2019Electrical, Electronic and Computer EngineeringMEngUnrestricte

Spectrum measurement, sensing, analysis and simulation in the context of cognitive radio

The radio frequency (RF) spectrum is a scarce natural resource, currently regulated locally by national agencies. Spectrum has been assigned to different services and it is very difficult for emerging wireless technologies to gain access due to rigid spectmm policy and heavy opportunity cost. Current spectrum management by licensing causes artificial spectrum scarcity. Spectrum monitoring shows that many frequencies and times are unused. Dynamic spectrum access (DSA) is a potential solution to low spectrum efficiency. In DSA, an unlicensed user opportunistically uses vacant licensed spectrum with the help of cognitive radio. Cognitive radio is a key enabling technology for DSA. In a cognitive radio system, an unlicensed Secondary User (SU) identifies vacant licensed spectrum allocated to a Primary User (PU) and uses it without harmful interference to the PU. Cognitive radio increases spectrum usage efficiency while protecting legacy-licensed systems. The purpose of this thesis is to bring together a group of CR concepts and explore how we can make the transition from conventional radio to cognitive radio. Specific goals of the thesis are firstly the measurement of the radio spectrum to understand the current spectrum usage in the Humber region, UK in the context of cognitive radio. Secondly, to characterise the performance of cyclostationary feature detectors through theoretical analysis, hardware implementation, and real-time performance measurements. Thirdly, to mitigate the effect of degradation due to multipath fading and shadowing, the use of -wideband cooperative sensing techniques using adaptive sensing technique and multi-bit soft decision is proposed, which it is believed will introduce more spectral opportunities over wider frequency ranges and achieve higher opportunistic aggregate throughput.Understanding spectrum usage is the first step toward the future deployment of cognitive radio systems. Several spectrum usage measurement campaigns have been performed, mainly in the USA and Europe. These studies show locality and time dependence. In the first part of this thesis a spectrum usage measurement campaign in the Humber region, is reported. Spectrum usage patterns are identified and noise is characterised. A significant amount of spectrum was shown to be underutilized and available for the secondary use. The second part addresses the question: how can you tell if a spectrum channel is being used? Two spectrum sensing techniques are evaluated: Energy Detection and Cyclostationary Feature Detection. The performance of these techniques is compared using the measurements performed in the second part of the thesis. Cyclostationary feature detection is shown to be more robust to noise. The final part of the thesis considers the identification of vacant channels by combining spectrum measurements from multiple locations, known as cooperative sensing. Wideband cooperative sensing is proposed using multi resolution spectrum sensing (MRSS) with a multi-bit decision technique. Next, a two-stage adaptive system with cooperative wideband sensing is proposed based on the combination of energy detection and cyclostationary feature detection. Simulations using the system above indicate that the two-stage adaptive sensing cooperative wideband outperforms single site detection in terms of detection success and mean detection time in the context of wideband cooperative sensing

Cooperative Radio Communications for Green Smart Environments

The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin

Multiservice Ethernet Digital Distributed Antenna Systems

Over 90% of wireless communications traffic occurs indoors and in-building wireless coverage is still one of the biggest obstacles for wireless users. As the growing demands on wireless capacity, coverage and connectivity have led to 4G and 5G standards, it has also become increasingly important to design and implement future-proof indoor wireless services in a cost effective manner. This thesis introduces a novel multi-service digital distributed antenna systems (DDAS) for indoor wireless coverage, which not only is able to transport multiple wireless carriers from different vendors and mobile operators, but also allows a converged architecture to integrate indoor wireless system with existing Ethernet infrastructures. The Cloud Radio Access Networks (C-RAN) has been suggested by major telecom vendors as the main architecture for last-mile coverage in 5G. However, the digital fronthaul interface defined in common public radio interface (CPRI), which is most widely adopted standard for C-RAN, requires very expensive infrastructures to be built due to the high data rate generated after digitisation. A solution has been introduced at the University of Cambridge previously to remove the digital redundancy by using a data compression technique which has shown 3-times higher transmission efficiency than CPRI. This thesis extends the concept to a more robust architecture allowing multiple wireless services to be transmitted simultaneously as well as being carried over standard Ethernet without losing the Quality of End-user Experience (QoE) and the Quality of Service (QoS) of in-building mobile network. A two-channel DDAS system with data compression algorithm is experimentally demonstrated, showing wide RF dynamic range for both 4G LTE service and 3G WCDMA service simultaneously carried over a single fibre-based infrastructure. The system leads to the design and implementation of full-service DDAS system allowing 14 channels (all 2/3/4G service from three major mobile operators) to be carried over single 10Gbps network. Typically, the system using CPRI will need over 30Gbps network to be installed for wireless coverage. Another key aspect covered in this thesis is the design and implementation of the multi-service DDAS over Ethernet (Eth-DDAS). Due to the stringent latency requirement in wireless services, mitigation of delays and errors in frame ordering has become a key challenge for putting DDAS over Ethernet. To overcome these problems, a special Eth-DDAS frame structure is proposed in this thesis. After digitisation, digital signal bearing RF information is packetised onto Ethernet-compatible frames with additional timestamps and sequence numbers before transported via fibre to the receiver. Three latency scenarios are tested with different payload sizes of the proposed frame structure and real-time RF performance is measured to prove the capability of implementation of such system in real-life using commercial off-the-shelf (COTS) ADC/DAC and FPGAs

Microwave resonant sensors

Microwave resonant sensors use the spectral characterisation of a resonator to make high sensitivity measurements of material electromagnetic properties at GHz frequencies. They have been applied to a wide range of industrial and scientific measurements, and used to study a diversity of physical phenomena. Recently, a number of challenging dynamic applications have been developed that require very high speed and high performance, such as kinetic inductance detectors and scanning microwave microscopes. Others, such as sensors for miniaturised fluidic systems and non-invasive blood glucose sensors, also require low system cost and small footprint. This thesis investigates new and improved techniques for implementing microwave resonant sensor systems, aiming to enhance their suitability for such demanding tasks. This was achieved through several original contributions: new insights into coupling, dynamics, and statistical properties of sensors; a hardware implementation of a realtime multitone readout system; and the development of efficient signal processing algorithms for the extraction of sensor measurements from resonator response data. The performance of this improved sensor system was verified through a number of novel measurements, achieving a higher sampling rate than the best available technology yet with equivalent accuracy and precision. At the same time, these experiments revealed unforeseen applications in liquid metrology and precision microwave heating of miniature flow systems.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Cooperative Radio Communications for Green Smart Environments

The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin

M-sequenze based ultra-wideband radar and its application to crack detection in salt mines

Die vorliegende Dissertation beschreibt einen innovativen ultra-breitband (UWB)elektromagnetischen Sensor basierend auf einem Pseudo-Rauschverfahren.Der Sensor wurde für zerstörungsfreies Testen in zivilen Anwendungen entwickelt.Zerstörungsfreies Testen entwickelt sich zu einem immer wichtiger werdenden Bereich in Forschung und Entwicklung. Neben unzähligen weiteren Anwendungen und Technologien, besteht ein primäres Aufgabenfeld in der Überwachung und Untersuchung von Bauwerken und Baumaterialien durch berührungslose Messung aus der Ferne.Diese Arbeit konzentriert sich auf das Beispiel der Auflockerungszone im Salzgestein.Der Hintergrund und die Notwendigkeit, den Zustand der oberflächennahen Salzschichten in Salzminen kennen zu müssen, werden beleuchtet und die Messaufgabe anhand einfacher theoretischer Überlegungen beschrieben. Daraus werden die Anforderungen für geeignete UWB Sensoren abgeleitet. Die wichtigsten Eigenschaften sind eine sehr hohe Messband breite sowie eine sehr saubere Systemimpulsantwort frei von systematischen Gerätefehlern. Beide Eigenschaften sind notwendig, um die schwachen Rückstreuungen der Auflockerungen trotz der unvermeidlichen starken Oberflächenreflexion detektieren zu können.Da systematische Fehler bei UWB Geräten technisch nicht von vorne herein komplett vermeidbar sind, muss der Sensor eine Gerätekalibrierung erlauben, um solche Fehler möglichst gut zu unterdrücken.Aufgrund der genannten Anforderungen und den Nebenbedingungen der Messumgebung unter Tage, wurde aus den verschiedenen UWB-Technologien ein Prinzip ausgewählt, welches pseudozufällige Maximalfolgen als Anregungssignal benutzt. Das M-Sequenzkonzept dient als Ausgangpunkt für zahlreiche Weiterentwicklungen. Ein neues Sendemodul erweitert dabei die Messbandbreite auf 12~GHz. Die äquivalente Abtastrate wird um den Faktor vier auf 36~GHz erhöht, ohne den geringen Abtastjitter des ursprünglichen Konzepts zu vergrössern.Weiterhin wird die Umsetzung eines Zweitormesskopfes zur Erfassung von S-Parametern sowie einer automatische Kalibriereinheit beschrieben. Etablierte Kalibrierverfahren aus dem Bereich der Netzwerkanalyse werden kurz rekapituliert und die Adaption des 8-Term Verfahrens mit unbekanntem Transmissionsnormal für das M-Sequenzsystem beschrieben. Dabei werden Kennwerte vorgeschlagen, die dem Bediener unter Tage einfach erlauben, die Kalibrierqualität einzuschätzen und Hinweise auf mögliche Gerätefehler oder andere Probleme zu bekommen. Die Kalibriergenauigkeit des neuen Sensors im Labor wird mit der eines Netzwerkanalysators verglichen. Beide Geräte erreichen eine störungsfreie Dynamik von mehr als 60~dB in den Systemimpulsantworten für Reflexion und Transmission.Der neu entwickelte UWB Sensor wurde in zahlreichen Messungen in Salzminen in Deutschland getestet. Zwei Messbeispiele werden vorgestellt - ein sehr alter, kreisrunder Tunnel sowie ein ovaler Tunnelstumpf, welcher kurz vor den Messungen erst aufgefahren wurde. Messaufbauten und Datenverarbeitung werden beschrieben. Schließlich werden Schlussfolgerungen und Vorschläge für zukünftige Arbeiten mit dem neuen M-Sequenzsensor sowie der Messung von Auflockerungen im Salzgestein diskutiert.This dissertation describes an innovative ultra-wideband (UWB) electromagnetic sensor device based on a pseudo-noise principle developed in the context of non-destructive testing in civil engineering.Non-destructive testing is becoming a more and more important fieldfor researchers and engineers alike. Besides the vast field of possibleapplications and testing technologies, a prime and therefore typical topic is the inspection and monitoringof constructions and materials by means of contactless remote sensing techniques.This work focuses on one example the assessment of the disaggregation zone in salt rock tunnels.The background and relevance of knowing the state of salt rock layers near a tunnel's surface are explainedand simple theoretical considerations for requirements of suitable UWB sensor devices are shown. The most important sensor parameters are a very large measurement bandwidth and a very clean impulse response. The latterparameter translates into the mandatory application of calibration techniques to remove systematic errors of the sensor system itself. This enables detection of weak scattering responses from near-surface disaggregation despite the presence of a strong surface reflection.According to the mentioned requirements and other side conditions in salt mine environments an UWB sensor principlebased on pseudo-noise stimuli namely M-Sequences is selected as a starting point for system development. A newtransmitter frontend for extending the stimulus bandwidth up to 12~GHz is presented. Furthermore, a technique for increasing the (equivalent) sampling rate while keeping the stable and low-jitter sampling regime of the M-Sequencesapproach is introduced and its implementation is shown. Moreover, an automatic calibration unit for full two-port coaxial calibration of the new UWB sensor has been developed. Common calibration techniques from the area of vector network analysers are shortly reviewed and a reasonablealgorithm the 8-term method with an unknown line standard - is selected for the M-Sequences device. The 8-term method is defined in the frequency domain and is adapted for use with time domain devices. Some performance figures and comparisonwith calibration results from network analysers are discussed to show the effectiveness of the calibration.A spurious-free dynamic range of the time domain impulse responses in excess of 60~dB has been achieved for reflection as well as transmission measurements.The new UWB sensor was used in various real world measurements in different salt mines throughout Germany. Two measurementexamples are described and results from the disaggregation zone of a very old and a freshly cut tunnel will be presented. Measurement setup and data processing are discussed and finally some conclusions for future work on this topic are drawn

Microwave resonant sensors

Microwave resonant sensors use the spectral characterisation of a resonator to make high sensitivity measurements of material electromagnetic properties at GHz frequencies. They have been applied to a wide range of industrial and scientific measurements, and used to study a diversity of physical phenomena. Recently, a number of challenging dynamic applications have been developed that require very high speed and high performance, such as kinetic inductance detectors and scanning microwave microscopes. Others, such as sensors for miniaturised fluidic systems and non-invasive blood glucose sensors, also require low system cost and small footprint. This thesis investigates new and improved techniques for implementing microwave resonant sensor systems, aiming to enhance their suitability for such demanding tasks. This was achieved through several original contributions: new insights into coupling, dynamics, and statistical properties of sensors; a hardware implementation of a realtime multitone readout system; and the development of efficient signal processing algorithms for the extraction of sensor measurements from resonator response data. The performance of this improved sensor system was verified through a number of novel measurements, achieving a higher sampling rate than the best available technology yet with equivalent accuracy and precision. At the same time, these experiments revealed unforeseen applications in liquid metrology and precision microwave heating of miniature flow systems