Effiziente Algorithmen der Positionsbestimmung und positionsbasierte Kontextgewinnung zur Selbstorganisation in drahtlosen Sensornetzwerken

Als zentrales Thema der Arbeit wird die Positionsbestimmung einzelner Knoten innerhalb drahtloser Sensornetzwerke betrachtet. Im zweiten Themenkomplex, der Clusterbildung, wird zum einen ein auf Lokalisierung aufbauendes Verfahren betrachtet. Zum anderen wird ein Algorithmus vorgestellt, welcher nicht auf die Ermittlung konkreter Positionen angewiesen ist. Das im dritten Themenkomplex betrachtete Verfahren zur Erkennung von Fehlern innerhalb drahtloser Sensornetzwerke bietet eine Möglichkeit, um Fehler innerhalb ermittelter Informationen in drahtlosen Sensornetzwerken zu erkennen.As its main topic this thesis deals with positioning of single nodes within wireless sensor networks. Clustering in wireless sensor networks forms the second part of this work. Two newly developed algorithms will be presented. One of them is based on location information. The other uses coarse grained localization technique but without the need for location information. The third topic of this thesis is about an algorithm newly developed to detect erroneous data at a sensor node

Least-Squares Based Adaptive Source Localization with Biomedical Applications

In this thesis, we study certain aspects of signal source/target localization by sensory agents and their biomedical applications. We first focus on a generic distance measurement based problem: Estimation of the location of a signal source by a sensory agent equiped with a distance measurement unit or a team of such a sensory agent. This problem was addressed in some recent studies using a gradient based adaptive algorithm. In this study, we design a least-squares based adaptive algorithm with forgetting factor for the same task. Besides its mathematical background, we perform some simulations for both stationary and drifting target cases. The least-squares based algorithm we propose bears the same asymptotic stability and convergence properties as the gradient algorithm previously studied. It is further demonstrated via simulation studies that the proposed least-squares algorithm converges significantly faster to the resultant location estimates than the gradient algorithm for high values of the forgetting factor, and significantly reduces the noise effects for small values of the forgetting factor. We also focus on the problem of localizing a medical device/implant in human body by a mobile sensor unit (MSU) using distance measurements. As the particular distance measurement method, time of flight (TOF) based approach involving ultra wide-band signals is used, noting the important effects of the medium characteristics on this measurement method. Since human body consists of different organs and tissues, each with a different signal permittivity coefficient and hence a different signal propagation speed, one cannot assume a constant signal propagation speed environment for the aforementioned medical localization problem. Furthermore, the propagation speed is unknown. Considering all the above factors and utilizing a TOF based distance measurement mechanism, we use the proposed adaptive least-square algorithm to estimate the 3-D location of a medical device/implant in the human body. In the design of the adaptive algorithm, we first derive a linear parametric model with the unknown 3-D coordinates of the device/implant and the current signal propagation speed of the medium as its parameters. Then, based on this parametric model, we design the proposed adaptive algorithm, which uses the measured 3-D position of the MSU and the measured TOF as regressor signals. After providing a formal analysis of convergence properties of the proposed localization algorithm, we implement numerical tests to analyze the properties of the localization algorithm, considering two types of scenarios: (1) A priori information regarding the region, e.g quadrant (among upper-left, upper-right, lower-left, lower-right of the human body), of the implant location is available and (2) such a priori information is not available. In (1), assuming knowledge of fixed average relative permittivity for each region, we established that the proposed algorithm converges to an estimate with zero estimation error. Moreover, different white Gaussian noises are added to emulate the TOF measurement disturbances, and it is observed that the proposed algorithm is robust to such noises/disturbances. In (2), although perfect estimation is not achieved, the estimation error is at a low admissible level. In addition, for both cases (1) and (2), forgetting factor effects have been investigated and results show that use of small forgetting factor values reduces noise effects significantly, while use of high forgetting factor values speeds up convergence of the estimation

Least-Squares Based Adaptive Source Localization with Biomedical Applications

In this thesis, we study certain aspects of signal source/target localization by sensory agents and their biomedical applications. We first focus on a generic distance measurement based problem: Estimation of the location of a signal source by a sensory agent equiped with a distance measurement unit or a team of such a sensory agent. This problem was addressed in some recent studies using a gradient based adaptive algorithm. In this study, we design a least-squares based adaptive algorithm with forgetting factor for the same task. Besides its mathematical background, we perform some simulations for both stationary and drifting target cases. The least-squares based algorithm we propose bears the same asymptotic stability and convergence properties as the gradient algorithm previously studied. It is further demonstrated via simulation studies that the proposed least-squares algorithm converges significantly faster to the resultant location estimates than the gradient algorithm for high values of the forgetting factor, and significantly reduces the noise effects for small values of the forgetting factor. We also focus on the problem of localizing a medical device/implant in human body by a mobile sensor unit (MSU) using distance measurements. As the particular distance measurement method, time of flight (TOF) based approach involving ultra wide-band signals is used, noting the important effects of the medium characteristics on this measurement method. Since human body consists of different organs and tissues, each with a different signal permittivity coefficient and hence a different signal propagation speed, one cannot assume a constant signal propagation speed environment for the aforementioned medical localization problem. Furthermore, the propagation speed is unknown. Considering all the above factors and utilizing a TOF based distance measurement mechanism, we use the proposed adaptive least-square algorithm to estimate the 3-D location of a medical device/implant in the human body. In the design of the adaptive algorithm, we first derive a linear parametric model with the unknown 3-D coordinates of the device/implant and the current signal propagation speed of the medium as its parameters. Then, based on this parametric model, we design the proposed adaptive algorithm, which uses the measured 3-D position of the MSU and the measured TOF as regressor signals. After providing a formal analysis of convergence properties of the proposed localization algorithm, we implement numerical tests to analyze the properties of the localization algorithm, considering two types of scenarios: (1) A priori information regarding the region, e.g quadrant (among upper-left, upper-right, lower-left, lower-right of the human body), of the implant location is available and (2) such a priori information is not available. In (1), assuming knowledge of fixed average relative permittivity for each region, we established that the proposed algorithm converges to an estimate with zero estimation error. Moreover, different white Gaussian noises are added to emulate the TOF measurement disturbances, and it is observed that the proposed algorithm is robust to such noises/disturbances. In (2), although perfect estimation is not achieved, the estimation error is at a low admissible level. In addition, for both cases (1) and (2), forgetting factor effects have been investigated and results show that use of small forgetting factor values reduces noise effects significantly, while use of high forgetting factor values speeds up convergence of the estimation

MIMO underwater acoustic communications over time-varying channels: from theory to practice

Despite more than 70% of our planet surface is covered by water, today the underwater world can still be considered largely unknown. Rivers, lakes, seas and oceans have always been a fundamental resource for human life development, but at the same time they have often represented natural obstacles very hard to surmount. The most impressive example is probably given by the ocean, whose vastness severely limited geographical explorations and discoveries for tens of centuries. Anyway, the growing curiosity about what happens below the water surface has gradually led man to immerse in this unknown environment, trying to overcome its inaccessibility and figure out its secrets. Underwater investigation and exploring have been increasingly supported by technology, advanced over time for different purposes (military, commercial, scientific). In this regard, providing a communication link between remote users has been recognized as one of the main issues to be addressed. The first significant solutions derived from the radio-frequency world, subject of study since the 19th century. Unfortunately both wired and wireless RF inspired signal propagation strategies were not evaluated as successful. The former ones, since considering the deployment of meters (up to kilometers) of cable in depth, were too costly and difficult, while the latter ones did not offer good performance in terms of communication range due to signal attenuation. An alternative way, examined with particular interest from the beginning of the 20th century, has been that one offered by acoustics. Actually, the study of sound and its propagation through different media has been an intriguing topic since the Old World Age, hence the attempt of messaging underwater has seemed to be a great opportunity to convey theoretical principles in a real application. In addition, not only humans but also marine animals use acoustic waves to communicate, even over several kilometers distances as demonstrated by whales. So, since already existing in nature, acoustic communications have been considered as potentially successful, furthermore representing an effective trade-off between feasibility and performance, especially if compared to the other electromagnetic signals-based methods. Communication over RF channels has been extensively investigated so as to become a mature technology. The thorough knowledge about OSI (Open Systems Interconnection) model physical layer issues has allowed the researchers attention to be drawn to the upper layers. Following this direction, the recent advances in technology in this field have been accomplished mainly due to novelties in networks managing rather than to enhancements in the signal propagation study. Moving to acoustics, unfortunately this approach results to be failing if applied in the underwater scenario, as the major challenges rise indeed from physics matters. The underwater environment is varied and variable, so understanding the mechanisms that govern the propagation of sound in water is a key element for the design of a well-performing communication system. In this sense, the physical layer has therefore regained the centrality that has been diminished in other contexts. The underwater acoustic communications can be adopted in a wide range of applications. The best-known are coastal monitoring, target detection, AUVs (Autonomous Underwater Vehicles) remote control, tsunami alarm, environmental data collection and transmission. Those ones are very specific activities, so the devices to be employed must sometimes meet very strict requirements. In this regard, the solutions commercially available provide good performance (that are paid in terms of high costs). On the other hand, the fact that hardware and software are usually copyrighted leads to have a closed system. Having reconfigurable devices is instead an opportunity to match the technology with the environment features and variations, especially in real-time applications. Recently, the need to overcome these constraints has encouraged the debate about underwater technology challenges. The work by Demirors et al. [1] reports an interesting discussion about the implementation of software-defined underwater acoustic networks (UWANs), highlighting how this solution can provide enhancements in terms of software portability, computational capacity, energy efficiency and real-time reconfigurability. Furthermore, the authors propose the architecture of a software-defined acoustic modem and evaluate its performance and capabilities with tank and lake experiments. Considering the comments outlined above, the following dissertation deals with the design of an acoustic communication system. The preliminary theoretical analysis regarding physical layer concerns, such as signal propagation and channel behavior, represents the starting point from which several proposals regarding the implementation of UWANs are introduced. In particular the context of Multiple-Input Multiple-Output (MIMO) communications is investigated, presenting several solutions about transmission schemes and receiver implementation. Furthermore, concerning UWANs management, some strategies for access and error control, established at the data link layer level, are detailed. It is worth highlighting that the goal of this contribution is not to present a disjointed discussion about the topics just listed. The objective is instead to propose practical solutions developed hand in hand with theory, making choices firstly by looking at what nature allows

Mining Safety and Sustainability I

Safety and sustainability are becoming ever bigger challenges for the mining industry with the increasing depth of mining. It is of great significance to reduce the disaster risk of mining accidents, enhance the safety of mining operations, and improve the efficiency and sustainability of development of mineral resource. This book provides a platform to present new research and recent advances in the safety and sustainability of mining. More specifically, Mining Safety and Sustainability presents recent theoretical and experimental studies with a focus on safety mining, green mining, intelligent mining and mines, sustainable development, risk management of mines, ecological restoration of mines, mining methods and technologies, and damage monitoring and prediction. It will be further helpful to provide theoretical support and technical support for guiding the normative, green, safe, and sustainable development of the mining industry