Deep reinforcement learning for automatic run-time adaptation of UWB PHY radio settings

Ultra-wideband technology has become increasingly popular for indoor localization and location-based services. This has led recent advances to be focused on reducing the ranging errors, whilst research focusing on enabling more reliable and energy efficient communication has been largely unexplored. The IEEE 802.15.4 UWB physical layer allows for several settings to be selected that influence the energy consumption, range, and reliability. Combined with the available link state diagnostics reported by UWB devices, there is an opportunity to dynamically select PHY settings based on the environment. To address this, we propose a deep Q-learning approach for enabling reliable UWB communication, maximizing packet reception rate (PRR) and minimizing energy consumption. Deep Q-learning is a good fit for this problem, as it is an inherently adaptive algorithm that responds to the environment. Validation in a realistic office environment showed that the algorithm outperforms traditional Q-learning, linear search and using a fixed PHY layer. We found that deep Q-learning achieves a higher average PRR and reduces the ranging error while using only 14% of the energy compared to a fixed PHY setting in a dynamic office environment.Comment: 13 pages, 9 figures, 9 tables and submitted to IEEE Transactions on Cognitive Communications and Networkin

In-Soil Measuring of Sugar Beet Yield Using UWB Radar Sensor System

Yield mapping is a basic entity of the Precision Farming concept and provides crucial information about the success of cultivation. Several approaches to site-specific yield recording during the sugar beet harvest are known. Most of them are based on the weighing of sugar beets together with soil tare. Another real-time yield mapping approach with the option of plant population counting is based on estimating the mass of individual sugar beets on the basis of their maximal diameter. The main goal of the research was to develop and evaluate a yield recording procedure based on radar technology, which will provide non-invasive in-soil detection and identification of single sugar beets in order to enable the counting of individual sugar beets and determining of the single sugar beet root mass. Further goals were to enhance the radar technology for other applications in the agriculture, as a general goal, and to define applicability restrictions of practical utilisation of the system for the sugar beet and similar crops. The research activities have been divided into laboratory and field experiments. The results of the laboratory experiments have provided valuable information about the measuring system’s behaviour, which enabled the successful field measurements. The used method allowed the identification and detection of 90% to 96% of sugar beets under test in the various field conditions, with correlation coefficients between real sugar beet positions and detected positions of about 99%, and average positioning error from 1,1 to 3,6 cm. The correlation coefficients between single sugar beet root masses and recorded reflected energy amounts were for the majority of tests over 70%, and the best results have been on the level close to 90%. This project was a joint venture of the Institute for Agricultural Engineering from Bonn and the Technical University of Ilmenau.Teilflächenspezifische Ertragsmessung von Zuckerrüben im Boden mittels UWB Radarsensorsystem Die Ertragskartierung ist ein wesentlicher Bestandteil des Konzeptes „Precision Farming“. Die Erntemasse von Kulturpflanzen ist für den Landwirt eine elementare Information über den Erfolg pflanzbaulicher Maßnahmen. Es sind mehrere Verfahren zur Ertragsermittlung von Zuckerrüben während der Ernte mit dem Bezug auf Teilflächen bekannt. Ein sensorischer Ansatz besteht in der Pflanzenzählung und Ermittlung der Masse der einzelnen Zuckerrüben über den maximalen Durchmesser. Das Hauptziel dieser Forschungsarbeiten war die Entwicklung und Bewertung eines berührungslosen Ertragserfassungssystems für Zuckerrüben, das teilflächenbasiert eine Zählung und Massebestimmung der Einzelrüben ermöglicht. Die weiteren Ziele bestanden in der Weiterentwicklung der Radartechnologie für andere Einsatzgebiete der Landwirtschaft und in der Bestimmung der Anwendbarkeitsgrenzen des Systems für Zuckerrüben und ähnliche Wurzelfrüchte. Die Forschungsaktivitäten fanden im Labor und unter Feldbedingungen auf Versuchsparzellen eines typischen Zuckerrübenstandortes statt. Die Ergebnisse unter Laborbedingungen lieferten wertvolle Informationen, die erfolgreiche Feldmessungen ermöglicht haben. Die angewendete Methode hat in unterschiedlichen Messbedingungen eine 90% bis 96% erfolgreiche Zuckerrübenidentifikation ermöglicht, mit Korrelationskoeffizienten zwischen tatsächlichen und detektierten Zuckerrübenpositionen von um 99% und einem durchschnittlichen Positionierungsfehler von 1,1 bis 3,6 cm. Die Korrelationskoeffizienten zwischen der Einzelrübenmasse und der gemessenen reflektierten Energiemenge lagen im Bereich von über 70% und die besten Ergebnisse erreichten Werte von 90%. Das Projekt wurde in der Zusammenarbeit des Instituts für Landtechnik Bonn und des Instituts für Kommunikations- und Messtechnik der Technischen Universität Ilmenau durchgeführt

Characterization of Ultra Wideband Multiple Access Performance Using Time Hopped-Biorthogonal Pulse Position Modulation

The FCC\u27s release of its UWB First Report and Order in April 2002 spawned renewed interest in impulse signaling research. This work combines Time Hopped (TH) multiple access coding with 4-ary UWB Biorthogonal Pulse Position Modulation (TH-BPPM). Multiple access performance is evaluated in a multipath environment for both synchronous and asynchronous networks. Fast time hopping is implemented by replicating and hopping each TH-BPPM symbol NH times. Bit error expressions are derived for biorthogonal TH-BPPM signaling and results compared with previous orthogonal TH-PPM work. Without fast time hopping (NH = 1), the biorthogonal TH-BPPM technique provided gains equivalent to Gray-coded QPSK; improved BER at a given Eb/No and an effective doubling of the data rate. A synchronized network containing up to NT = 15 transmitters yields an average BER improvement (relative to an asynchronous network) of approximately -6.30 dB with orthogonal TH-PPM and approximately 5.9 dB with biorthogonal TH-BPPM. Simulation results indicate that doubling the number of multipath replications (NMP) reduces BER by approximately 3.6 dB. Network performance degrades as NT and NMP increase and synchronized network advantages apparent in the NMP = 0 case diminish with multipath interference present. With fast time hopping (NH \u3e 1) improves BER performance whenever NMP \u3c NH while reducing effective data rate by 1/NH. Compared to the NH = 1 synchronized network, TH-BPPM modulation using NH = 10 provides approximately 5.9 dB improvement at NMP = 0 and approximately 3.6 dB improvement at NMP = 5. At NMP = 10, the BER for the hopped and NH = 1 cases are not statistically different; with NH = 10 hops, BER improvement varies from approximately 0.57 to 0.14 dB (minimal variation between synchronous and asynchronous network performance)

Localisation and tracking of people using distributed UWB sensors

In vielen Überwachungs- und Rettungsszenarien ist die Lokalisierung und Verfolgung von Personen in Innenräumen auf nichtkooperative Weise erforderlich. Für die Erkennung von Objekten durch Wände in kurzer bis mittlerer Entfernung, ist die Ultrabreitband (UWB) Radartechnologie aufgrund ihrer hohen zeitlichen Auflösung und Durchdringungsfähigkeit Erfolg versprechend. In dieser Arbeit wird ein Prozess vorgestellt, mit dem Personen in Innenräumen mittels UWB-Sensoren lokalisiert werden können. Er umfasst neben der Erfassung von Messdaten, Abstandschätzungen und dem Erkennen von Mehrfachzielen auch deren Ortung und Verfolgung. Aufgrund der schwachen Reflektion von Personen im Vergleich zum Rest der Umgebung, wird zur Personenerkennung zuerst eine Hintergrundsubtraktionsmethode verwendet. Danach wird eine konstante Falschalarmrate Methode zur Detektion und Abstandschätzung von Personen angewendet. Für Mehrfachziellokalisierung mit einem UWB-Sensor wird eine Assoziationsmethode entwickelt, um die Schätzungen des Zielabstandes den richtigen Zielen zuzuordnen. In Szenarien mit mehreren Zielen kann es vorkommen, dass ein näher zum Sensor positioniertes Ziel ein anderes abschattet. Ein Konzept für ein verteiltes UWB-Sensornetzwerk wird vorgestellt, in dem sich das Sichtfeld des Systems durch die Verwendung mehrerer Sensoren mit unterschiedlichen Blickfeldern erweitert lässt. Hierbei wurde ein Prototyp entwickelt, der durch Fusion von Sensordaten die Verfolgung von Mehrfachzielen in Echtzeit ermöglicht. Dabei spielen insbesondere auch Synchronisierungs- und Kooperationsaspekte eine entscheidende Rolle. Sensordaten können durch Zeitversatz und systematische Fehler gestört sein. Falschmessungen und Rauschen in den Messungen beeinflussen die Genauigkeit der Schätzergebnisse. Weitere Erkenntnisse über die Zielzustände können durch die Nutzung zeitlicher Informationen gewonnen werden. Ein Mehrfachzielverfolgungssystem wird auf der Grundlage des Wahrscheinlichkeitshypothesenfilters (Probability Hypothesis Density Filter) entwickelt, und die Unterschiede in der Systemleistung werden bezüglich der von den Sensoren ausgegebene Informationen, d.h. die Fusion von Ortungsinformationen und die Fusion von Abstandsinformationen, untersucht. Die Information, dass ein Ziel detektiert werden sollte, wenn es aufgrund von Abschattungen durch andere Ziele im Szenario nicht erkannt wurde, wird als dynamische Überdeckungswahrscheinlichkeit beschrieben. Die dynamische Überdeckungswahrscheinlichkeit wird in das Verfolgungssystem integriert, wodurch weniger Sensoren verwendet werden können, während gleichzeitig die Performanz des Schätzers in diesem Szenario verbessert wird. Bei der Methodenauswahl und -entwicklung wurde die Anforderung einer Echtzeitanwendung bei unbekannten Szenarien berücksichtigt. Jeder untersuchte Aspekt der Mehrpersonenlokalisierung wurde im Rahmen dieser Arbeit mit Hilfe von Simulationen und Messungen in einer realistischen Umgebung mit UWB Sensoren verifiziert.Indoor localisation and tracking of people in non-cooperative manner is important in many surveillance and rescue applications. Ultra wideband (UWB) radar technology is promising for through-wall detection of objects in short to medium distances due to its high temporal resolution and penetration capability. This thesis tackles the problem of localisation of people in indoor scenarios using UWB sensors. It follows the process from measurement acquisition, multiple target detection and range estimation to multiple target localisation and tracking. Due to the weak reflection of people compared to the rest of the environment, a background subtraction method is initially used for the detection of people. Subsequently, a constant false alarm rate method is applied for detection and range estimation of multiple persons. For multiple target localisation using a single UWB sensor, an association method is developed to assign target range estimates to the correct targets. In the presence of multiple targets it can happen that targets closer to the sensor induce shadowing over the environment hindering the detection of other targets. A concept for a distributed UWB sensor network is presented aiming at extending the field of view of the system by using several sensors with different fields of view. A real-time operational prototype has been developed taking into consideration sensor cooperation and synchronisation aspects, as well as fusion of the information provided by all sensors. Sensor data may be erroneous due to sensor bias and time offset. Incorrect measurements and measurement noise influence the accuracy of the estimation results. Additional insight of the targets states can be gained by exploiting temporal information. A multiple person tracking framework is developed based on the probability hypothesis density filter, and the differences in system performance are highlighted with respect to the information provided by the sensors i.e. location information fusion vs range information fusion. The information that a target should have been detected when it is not due to shadowing induced by other targets is described as dynamic occlusion probability. The dynamic occlusion probability is incorporated into the tracking framework, allowing fewer sensors to be used while improving the tracker performance in the scenario. The method selection and development has taken into consideration real-time application requirements for unknown scenarios at every step. Each investigated aspect of multiple person localization within the scope of this thesis has been verified using simulations and measurements in a realistic environment using M-sequence UWB sensors

Advanced ultrawideband imaging algorithms for breast cancer detection

Ultrawideband (UWB) technology has received considerable attention in recent years as it is regarded to be able to revolutionise a wide range of applications. UWB imaging for breast cancer detection is particularly promising due to its appealing capabilities and advantages over existing techniques, which can serve as an early-stage screening tool, thereby saving millions of lives. Although a lot of progress has been made, several challenges still need to be overcome before it can be applied in practice. These challenges include accurate signal propagation modelling and breast phantom construction, artefact resistant imaging algorithms in realistic breast models, and low-complexity implementations. Under this context, novel solutions are proposed in this thesis to address these key bottlenecks. The thesis first proposes a versatile electromagnetic computational engine (VECE) for simulating the interaction between UWB signals and breast tissues. VECE provides the first implementation of its kind combining auxiliary differential equations (ADE) and convolutional perfectly matched layer (CPML) for describing Debye dispersive medium, and truncating computational domain, respectively. High accuracy and improved computational and memory storage efficiency are offered by VECE, which are validated via extensive analysis and simulations. VECE integrates the state-of-the-art realistic breast phantoms, enabling the modelling of signal propagation and evaluation of imaging algorithms. To mitigate the severe interference of artefacts in UWB breast cancer imaging, a robust and artefact resistant (RAR) algorithm based on neighbourhood pairwise correlation is proposed. RAR is fully investigated and evaluated in a variety of scenarios, and compared with four well-known algorithms. It has been shown to achieve improved tumour detection and robust artefact resistance over its counterparts in most cases, while maintaining high computational efficiency. Simulated tumours in both homogeneous and heterogeneous breast phantoms with mild to moderate densities, combined with an entropy-based artefact removal algorithm, are successfully identified and localised. To further improve the performance of algorithms, diverse and dynamic correlation weighting factors are investigated. Two new algorithms, local coherence exploration (LCE) and dynamic neighbourhood pairwise correlation (DNPC), are presented, which offer improved clutter suppression and image resolution. Moreover, a multiple spatial diversity (MSD) algorithm, which explores and exploits the richness of signals among different transmitter and receiver pairs, is proposed. It is shown to achieve enhanced tumour detection even in severely dense breasts. Finally, two accelerated image reconstruction mechanisms referred to as redundancy elimination (RE) and annulus predication (AP) are proposed. RE removes a huge number of repetitive operations, whereas AP employs a novel annulus prediction to calculate millions of time delays in a highly efficient batch mode. Their efficacy is demonstrated by extensive analysis and simulations. Compared with the non-accelerated method, RE increases the computation speed by two-fold without any performance loss, whereas AP can be 45 times faster with negligible performance degradation

Modeling the Behavior of Multipath Components Pertinent to Indoor Geolocation

Recently, a number of empirical models have been introduced in the literature for the behavior of direct path used in the design of algorithms for RF based indoor geolocation. Frequent absence of direct path has been a major burden on the performance of these algorithms directing researchers to discover algorithms using multipath diversity. However, there is no reliable model for the behavior of multipath components pertinent to precise indoor geolocation. In this dissertation, we first examine the absence of direct path by statistical analysis of empirical data. Then we show how the concept of path persistency can be exploited to obtain accurate ranging using multipath diversity. We analyze the effects of building architecture on the multipath structure by demonstrating the effects of wall length and wall density on the path persistency. Finally, we introduce a comprehensive model for the spatial behavior of multipath components. We use statistical analysis of empirical data obtained by a measurement calibrated ray-tracing tool to model the time-of- arrival, angle-of-arrival and path gains. The relationship between the transmitter-receiver separation and the number of paths are also incorporated in our model. In addition, principles of ray optics are applied to explain the spatial evolution of path gains, time-of-arrival and angle-of-arrival of individual multipath components as a mobile terminal moves inside a typical indoor environment. We also use statistical modeling for the persistency and birth/death rate of the paths

Radar Technology

In this book “Radar Technology”, the chapters are divided into four main topic areas: Topic area 1: “Radar Systems” consists of chapters which treat whole radar systems, environment and target functional chain. Topic area 2: “Radar Applications” shows various applications of radar systems, including meteorological radars, ground penetrating radars and glaciology. Topic area 3: “Radar Functional Chain and Signal Processing” describes several aspects of the radar signal processing. From parameter extraction, target detection over tracking and classification technologies. Topic area 4: “Radar Subsystems and Components” consists of design technology of radar subsystem components like antenna design or waveform design