Entwicklung und Implementierung eines Peer-to-Peer Kalman Filters für Fußgänger- und Indoor-Navigation

Smartphones are an integral part of our society by now. They are used for messaging, searching the Internet, working on documents, and of course for navigation. Although smartphones are also used for car navigation their main area of application is pedestrian navigation. Almost all smartphones sold today comprise a GPS L1 receiver which provides position computation with accuracy between 1 and 10 m as long as the environment in beneficial, i.e. the line-of-sight to satellites is not obstructed by trees or high buildings. But this is often the case in areas where smartphones are used primarily for navigation. Users walk in narrow streets with high density, in city centers, enter, and leave buildings and the smartphone is not able to follow their movement because it loses satellite signals. The approach presented in this thesis addresses the problem to enable seamless navigation for the user independently of the current environment and based on cooperative positioning and inertial navigation. It is intended to realize location-based services in areas and buildings with limited or no access to satellite data and a large amount of users like e.g. shopping malls, city centers, airports, railway stations and similar environments. The idea of this concept was for a start based on cooperative positioning between users’ devices denoted here as peers moving within an area with only limited access to satellite signals at certain places (windows, doors) or no access at all. The devices are therefore not able to provide a position by means of satellite signals. Instead of deploying solutions based on infrastructure, surveying, and centralized computations like range measurements, individual signal strength, and similar approaches a decentralized concept was developed. This concept suggests that the smartphone automatically detects if no satellite signals are available and uses its already integrated inertial sensors like magnetic field sensor, accelerometer, and gyroscope for seamless navigation. Since the quality of those sensors is very low the accuracy of the position estimation decreases with each step of the user. To avoid a continuously growing bias between real position and estimated position an update has to be performed to stabilize the position estimate. This update is either provided by the computation of a position based on satellite signals or if signals are not available by the exchange of position data with another peer in the near vicinity using peer-to-peer ad-hoc networks. The received and the own position are processed in a Kalman Filter algorithm and the result is then used as new position estimate and new start position for further navigation based on inertial sensors. The here presented concept is therefore denoted as Peer-to-Peer Kalman Filter (P2PKF)

Development and Experimental Analysis of Wireless High Accuracy Ultra-Wideband Localization Systems for Indoor Medical Applications

This dissertation addresses several interesting and relevant problems in the field of wireless technologies applied to medical applications and specifically problems related to ultra-wideband high accuracy localization for use in the operating room. This research is cross disciplinary in nature and fundamentally builds upon microwave engineering, software engineering, systems engineering, and biomedical engineering. A good portion of this work has been published in peer reviewed microwave engineering and biomedical engineering conferences and journals. Wireless technologies in medicine are discussed with focus on ultra-wideband positioning in orthopedic surgical navigation. Characterization of the operating room as a medium for ultra-wideband signal transmission helps define system design requirements. A discussion of the first generation positioning system provides a context for understanding the overall system architecture of the second generation ultra-wideband positioning system outlined in this dissertation. A system-level simulation framework provides a method for rapid prototyping of ultra-wideband positioning systems which takes into account all facets of the system (analog, digital, channel, experimental setup). This provides a robust framework for optimizing overall system design in realistic propagation environments. A practical approach is taken to outline the development of the second generation ultra-wideband positioning system which includes an integrated tag design and real-time dynamic tracking of multiple tags. The tag and receiver designs are outlined as well as receiver-side digital signal processing, system-level design support for multi-tag tracking, and potential error sources observed in dynamic experiments including phase center error, clock jitter and drift, and geometric position dilution of precision. An experimental analysis of the multi-tag positioning system provides insight into overall system performance including the main sources of error. A five base station experiment shows the potential of redundant base stations in improving overall dynamic accuracy. Finally, the system performance in low signal-to-noise ratio and non-line-of-sight environments is analyzed by focusing on receiver-side digitally-implemented ranging algorithms including leading-edge detection and peak detection. These technologies are aimed at use in next-generation medical systems with many applications including surgical navigation, wireless telemetry, medical asset tracking, and in vivo wireless sensors

Real-Time Localization Using Software Defined Radio

Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system

Enhanced receiver architectures for processing multi GNSS signals in a single chain : based on partial differential equations mathematical model

The focus of our research is on designing a new architecture (RF front-end and digital) for processing multi GNSS signals in a single receiver chain. The motivation is to save in overhead cost (size, processing time and power consumption) of implementing multiple signal receivers side-by-side on-board Smartphones. This thesis documents the new multi-signal receiver architecture that we have designed. Based on this architecture, we have achieved/published eight novel contributions. Six of these implementations focus on multi GNSS signal receivers, and the last two are for multiplexing Bluetooth and GPS received signals in a single processing chain. We believe our work in terms of the new innovative and novel techniques achieved is a major contribution to the commercial world especially that of Smartphones. Savings in both silicon size and processing time will be highly beneficial to reduction of costs but more importantly for conserving the energy of the battery. We are proud that we have made this significant contribution to both industry and the scientific research and development arena. The first part of the work focus on the Two GNSS signal detection front-end approaches that were designed to explore the availability of the L1 band of GPS, Galileo and GLONASS at an early stage. This is so that the receiver devotes appropriate resources to acquire them. The first approach was based on folding the carrier frequency of all the three GNSS signals with their harmonics to the First Nyquist Zone (FNZ), as depicted by the BandPass Sampling Receiver technique (BPSR). Consequently, there is a unique power distribution of these folded signals based on the actual present signals that can be detected to alert the digital processing parts to acquire it. Volterra Series model is used to estimate the existing power in the FNZ by extracting the kernels of these folded GNSS signals, if available. The second approach filters out the right-side lobe of the GLONASS signal and the left-side lobe of the Galileo signal, prior to the folding process in our BPSR implementation. This filtering is important to enable none overlapped folding of these two signals with the GPS signal in the FNZ. The simulation results show that adopting these two approaches can save much valuable acquisition processing time. Our Orthogonal BandPass Sampling Receiver and Orthogonal Complex BandPass Sampling Receiver are two methods designed to capture any two wireless signals simultaneously and use a single channel in the digital domain to process them, including tracking and decoding, concurrently. The novelty of the two receivers is centred on the Orthogonal Integrated Function (OIF) that continuously harmonies the two received signals to form a single orthogonal signal allowing the “tracking and decoding” to be carried out by a single digital channel. These receivers employ a Hilbert Transform for shifting one of the input signals by 90-degrees. Then, the BPSR technique is used to fold back the two received signals to the same reference frequency in the FNZ. Results show that these designed methods also reduce the sampling frequency to a rate proportional to the maximum bandwidth, instead of the summation of bandwidths, of the input signals. Two combined GPS L1CA and L2C signal acquisition channels are designed based on applying the idea of the OIF to enhance the power consumption and the implementation complexity in the existing combination methods and also to enhance the acquisition sensitivity. This is achieved by removing the Doppler frequency of the two signals; our methods add the in-phase component of the L2C signal together with the in-phase component of the L1CA signal, which is then shifted by 90-degree before adding it to the remaining components of these two signals, resulting in an orthogonal form of the combined signals. This orthogonal signal is then fed to our developed version of the parallel-code-phase-search engine. Our simulation results illustrate that the acquisition sensitivity of these signals is improved successfully by 5.0 dB, which is necessary for acquiring weak signals in harsh environments. The last part of this work focuses on the tracking stage when specifically multiplexing Bluetooth and L1CA GPS signals in a single channel based on using the concept of the OIF, where the tracking channel can be shared between the two signals without losing the lock or degrading its performance. Two approaches are designed for integrating the two signals based on the mathematical analysis of the main function of the tracking channel, which the Phase-Locked Loop (PLL). A mathematical model of a set of differential equations has been developed to evaluate the PLL when it used to track and demodulated two signals simultaneously. The simulation results proved that the implementation of our approaches has reduced by almost half the size and processing time

Advanced Trends in Wireless Communications

Physical limitations on wireless communication channels impose huge challenges to reliable communication. Bandwidth limitations, propagation loss, noise and interference make the wireless channel a narrow pipe that does not readily accommodate rapid flow of data. Thus, researches aim to design systems that are suitable to operate in such channels, in order to have high performance quality of service. Also, the mobility of the communication systems requires further investigations to reduce the complexity and the power consumption of the receiver. This book aims to provide highlights of the current research in the field of wireless communications. The subjects discussed are very valuable to communication researchers rather than researchers in the wireless related areas. The book chapters cover a wide range of wireless communication topics

Timing and Carrier Synchronization in Wireless Communication Systems: A Survey and Classification of Research in the Last 5 Years

Timing and carrier synchronization is a fundamental requirement for any wireless communication system to work properly. Timing synchronization is the process by which a receiver node determines the correct instants of time at which to sample the incoming signal. Carrier synchronization is the process by which a receiver adapts the frequency and phase of its local carrier oscillator with those of the received signal. In this paper, we survey the literature over the last 5 years (2010–2014) and present a comprehensive literature review and classification of the recent research progress in achieving timing and carrier synchronization in single-input single-output (SISO), multiple-input multiple-output (MIMO), cooperative relaying, and multiuser/multicell interference networks. Considering both single-carrier and multi-carrier communication systems, we survey and categorize the timing and carrier synchronization techniques proposed for the different communication systems focusing on the system model assumptions for synchronization, the synchronization challenges, and the state-of-the-art synchronization solutions and their limitations. Finally, we envision some future research directions

Emerging Communications for Wireless Sensor Networks

Wireless sensor networks are deployed in a rapidly increasing number of arenas, with uses ranging from healthcare monitoring to industrial and environmental safety, as well as new ubiquitous computing devices that are becoming ever more pervasive in our interconnected society. This book presents a range of exciting developments in software communication technologies including some novel applications, such as in high altitude systems, ground heat exchangers and body sensor networks. Authors from leading institutions on four continents present their latest findings in the spirit of exchanging information and stimulating discussion in the WSN community worldwide

Computational Algorithm for Dynamic Hybrid Bayesian Network in On-line System Health Management Applications

With the increasing complexity of today's engineering systems that contain various component dependencies and degradation behaviors, there has been increasing interest in on-line System Health Management (SHM) capability to continuously monitor (via sensors and other methods of observation) system software, and hardware components for detection and diagnostic of safety-critical systems. Bayesian Network (BN) and their extension for time-series modeling known as Dynamic Bayesian Network (DBN) have been shown by recent studies to be capable of providing a unified framework for system health diagnosis and prognosis. BN has many modeling features, such as multi-state variables, noisy gates, dependent failures, and general posterior analysis. BN also allows a compact representation of the temporal and functional dependencies among system components. However, one of the barriers to applying BN in real-world problems is limitation in adequately handle "hybrid models", which contain both discrete and continuous variables, with both static and time-dependent failure distributions. This research presents a new modeling approach, computational algorithm, and an example application for health monitoring and learning in on-line SHM. A hybrid DBN is introduced to represent complex engineering systems with underlying physics of failure by modeling a theoretical or empirical degradation model with continuous variables. The methodology is designed to be flexible and intuitive, and scalable from small, localized functionality to large complex dynamic systems. Markov Chain Monte Carlo (MCMC) inference is optimized using a pre-computation strategy and dynamic programming for on-line monitoring of system health. Proposed Monitoring and Anomaly Detection algorithm uses pattern recognition to improve failure detection and estimation of Remaining Useful Life (RUL). Pre-computation inference database enables efficient on-line learning and maintenance decision-making. The scope of this research includes a new modeling approach, computation algorithm, and an example application for on-line SHM