Array imperfection calibration for wireless channel multipath characterisation

As one of the fastest growing technologies in modern telecommunications, wireless networking has become a very important and indispensable part in our life. A good understanding of the wireless channel and its key physical parameters are extremely useful when we want to apply them into practical applications. In wireless communications, the wireless channel refers to the propagation of electromagnetic radiation from a transmitter to a receiver. The estimation of multipath channel parameters, such as angle of depature (AoD), angle of arrival (AoA), and time difference of arrival (TDoA), is an active research problem and its typical applications are radar, communication, vehicle navigation and localization in the indoor environment where the GPS service is impractical. However, the performance of the parameter estimation deteriorates significantly in the presence of array imperfections, which include the mutual coupling, antenna location error, phase uncertainty and so on. These array imperfections are hardly to be calibrated completely via antenna design. In this thesis, we experimentally evaluate an B matrix method to cope with these array imperfection, our results shows a great improvement of AoA estimation results

Two-dimensional angular parameter estimation for noncircular incoherently distributed sources based on an L-shaped array

In this paper, a two-stage reduced-rank estimator is proposed for two-dimensional (2D) direction estimation of incoherently distributed (ID) noncircular sources, including their center directions of arrival (DOAs) and angular spreads, based on an L-shaped array. Firstly, based on the first-order Taylor series approximation, a noncircularity-based extended generalized array manifold (GAM) model is established. Then, the 2D center DOAs of incident ID signals are obtained separately with the noncircularity-based generalized shift-invariance property of the array manifold and the reduced-rank principle. The pairing of the two center DOAs is completed by searching for the minimum value of a cost function. Secondly, the 2D angular spreads can be obtained in closed-form solution from the central moments of the angular distribution. The proposed estimator achieves higher accuracy in angle estimation that manages more sources and shows promising results in the general scenario, where different sources possess different angular distributions. Furthermore, the approximate noncircular stochastic Cramer-Rao bound (CRB) of the concerned problem is derived as a benchmark. Numerical analysis proves that the proposed algorithm achieves better estimation performance in both 2D center DOAs and 2D angular spreads than an existing estimator

時間と周波数領域情報に基づいたシステムモデリングとその応用

System modeling is required to deal with the time-varying system dynamics or the experimental data with insufficient information. However, the existing methods cannot construct satisfactory models for rapidly varying systems or severely band-limited signals. This thesis focuses on the new approaches to solve such system modeling problems based on time and frequency-domain information and illustrates their applications in time-varying channel identification and localization system. For the rapid time-varying systems, parameters can be approximated by the cosine series using virtual even periodic functions. Following the orthogonality of the trigonometric functions, the parameter estimation is recursively implemented by estimating the coefficients of each degree of the cosine harmonic term. For the localization system with insufficient frequency components, the spectral characteristics including phase information in frequency domain and the information evaluation in time domain are applied to improve the convergence performance. Numerical simulations demonstrate the effectiveness of the new approaches.北九州市立大

Angle-of-Arrival Measurement Techniques for Enhanced Positioning in Beyond 5G Systems

The new generation of mobile communication systems introduces new methods and technologies that may enhance positioning accuracy in some scenarios when the GNSS system cannot meet the requirements, such as indoor positioning and outdoor autonomous driving. The 3GPP standard and for the first time included the angle measurement as new positioning methods in 5G. The Angle of Arrival (AoA) is the angle measurement method on the uplink direction that can enjoy the new capabilities in 5G systems to enhance the positioning downs to centimeters.The new generation of mobile communication systems introduces new methods and technologies that may enhance positioning accuracy in some scenarios when the GNSS system cannot meet the requirements, such as indoor positioning and outdoor autonomous driving. The 3GPP standard and for the first time included the angle measurement as new positioning methods in 5G. The Angle of Arrival (AoA) is the angle measurement method on the uplink direction that can enjoy the new capabilities in 5G systems to enhance the positioning downs to centimeters. Multiple Signal Classification Method (MUSIC) is a high-accuracy super-resolution algorithm for AoA estimation. The MUSIC method for estimating AoA has many shortcomings that make it unsuitable for a wide variety of scenarios. Correlated multipath signals substantially reduce estimation accuracy. Additionally, this method is a searching algorithm that requires a significant amount of time to resolve AoA. In this thesis, a CASCADE algorithm was proposed to overcome MUSIC's constraints by estimating a coarse range of AoA using a rapid AoA algorithm and then passing that range to the second stage represented by MUSIC to estimate AoA correctly. Multipath signals were eliminated by modifying the proposed CASCADE to detect only the line of sight (LOS), which is the essential path for angular localization. Additionally, the thesis compares many AoA algorithms in the context of 5G systems. A sounding reference signal (SRS) in the mm-wave band was generated according to the 3GPP standards and utilized as the input to those algorithms. A simulation was conducted throughout this thesis by evaluating six AoA algorithms: Bartlet Beamforming, MVDR, MUSIC, ESPRIT, FFT, and the proposed CASCADE method. The results showed that the proposed algorithm achieves the best performance when using less than 64 array antenna elements. On the other hand, FFT alone can provide high accuracy when using an ultra massive antenna system (e.g., 256,512,1024). Additionally, the findings observed the effect of key parameters on the performance of AoA algorithms, such as low SNR, a small number of snapshots (samples), and the effect of multipath signals

Super Resolution Algorithms for Indoor Positioning Systems

Ph.DDOCTOR OF PHILOSOPH

Modelling, Simulation and Data Analysis in Acoustical Problems

Modelling and simulation in acoustics is currently gaining importance. In fact, with the development and improvement of innovative computational techniques and with the growing need for predictive models, an impressive boost has been observed in several research and application areas, such as noise control, indoor acoustics, and industrial applications. This led us to the proposal of a special issue about “Modelling, Simulation and Data Analysis in Acoustical Problems”, as we believe in the importance of these topics in modern acoustics’ studies. In total, 81 papers were submitted and 33 of them were published, with an acceptance rate of 37.5%. According to the number of papers submitted, it can be affirmed that this is a trending topic in the scientific and academic community and this special issue will try to provide a future reference for the research that will be developed in coming years

Sensor Signal and Information Processing II

In the current age of information explosion, newly invented technological sensors and software are now tightly integrated with our everyday lives. Many sensor processing algorithms have incorporated some forms of computational intelligence as part of their core framework in problem solving. These algorithms have the capacity to generalize and discover knowledge for themselves and learn new information whenever unseen data are captured. The primary aim of sensor processing is to develop techniques to interpret, understand, and act on information contained in the data. The interest of this book is in developing intelligent signal processing in order to pave the way for smart sensors. This involves mathematical advancement of nonlinear signal processing theory and its applications that extend far beyond traditional techniques. It bridges the boundary between theory and application, developing novel theoretically inspired methodologies targeting both longstanding and emergent signal processing applications. The topic ranges from phishing detection to integration of terrestrial laser scanning, and from fault diagnosis to bio-inspiring filtering. The book will appeal to established practitioners, along with researchers and students in the emerging field of smart sensors processing

Abstracts on Radio Direction Finding (1899 - 1995)

The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity