Spatial Identification Methods and Systems for RFID Tags

Disertační práce je zaměřena na metody a systémy pro měření vzdálenosti a lokalizaci RFID tagů pracujících v pásmu UHF. Úvod je věnován popisu současného stavu vědeckého poznání v oblasti RFID prostorové identifikace a stručnému shrnutí problematiky modelování a návrhu prototypů těchto systémů. Po specifikaci cílů disertace pokračuje práce popisem teorie modelování degenerovaného kanálu pro RFID komunikaci. Detailně jsou rozebrány metody měření vzdálenosti a odhadu směru příchodu signálu založené na zpracování fázové informace. Pro účely lokalizace je navrženo několik scénářů rozmístění antén. Modely degenerovaného kanálu jsou simulovány v systému MATLAB. Významná část této práce je věnována konceptu softwarově definovaného rádia (SDR) a specifikům jeho adaptace na UHF RFID, která využití běžných SDR systémů značně omezují. Diskutována je zejména problematika průniku nosné vysílače do přijímací cesty a požadavky na signál lokálního oscilátoru používaný pro směšování. Prezentovány jsou tři vyvinuté prototypy: experimentální dotazovač EXIN-1, měřicí systém založený na platformě Ettus USRP a anténní přepínací matice pro emulaci SIMO systému. Závěrečná část je zaměřena na testování a zhodnocení popisovaných lokalizačních technik, založených na měření komplexní přenosové funkce RFID kanálu. Popisuje úzkopásmové/širokopásmové měření vzdálenosti a metody odhadu směru signálu. Oba navržené scénáře rozmístění antén jsou v závěru ověřeny lokalizačním měřením v reálných podmínkách.The doctoral thesis is focused on methods and systems for ranging and localization of RFID tags operating in the UHF band. It begins with a description of the state of the art in the field of RFID positioning with short extension to the area of modeling and prototyping of such systems. After a brief specification of dissertation objectives, the thesis overviews the theory of degenerate channel modeling for RFID communication. Details are given about phase-based ranging and direction of arrival finding methods. Several antenna placement scenarios are proposed for localization purposes. The degenerate channel models are simulated in MATLAB. A significant part of the thesis is devoted to software defined radio (SDR) concept and its adaptation for UHF RFID operation, as it has its specialties which make the usage of standard SDR test equipment very disputable. Transmit carrier leakage into receiver path and requirements on local oscillator signals for mixing are discussed. The development of three experimental prototypes is also presented there: experimental interrogator EXIN-1, measurement system based on Ettus USRP platform, and antenna switching matrix for an emulation of SIMO system. The final part is focused on testing and evaluation of described positioning techniques based on complex backscatter channel transfer function measurement. Both narrowband/wideband ranging and direction of arrival methods are validated. Finally, both proposed antenna placement scenarios are evaluated with real-world measurements.

A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles

In recent years, there has been a dramatic increase in the use of unmanned aerial vehicles (UAVs), particularly for small UAVs, due to their affordable prices, ease of availability, and ease of operability. Existing and future applications of UAVs include remote surveillance and monitoring, relief operations, package delivery, and communication backhaul infrastructure. Additionally, UAVs are envisioned as an important component of 5G wireless technology and beyond. The unique application scenarios for UAVs necessitate accurate air-to-ground (AG) propagation channel models for designing and evaluating UAV communication links for control/non-payload as well as payload data transmissions. These AG propagation models have not been investigated in detail when compared to terrestrial propagation models. In this paper, a comprehensive survey is provided on available AG channel measurement campaigns, large and small scale fading channel models, their limitations, and future research directions for UAV communication scenarios

Route diversity analyses for free-space optical wireless links within turbulent scenarios

Free-Space Optical (FSO) communications link performance is highly affected when propagating through the time-spatially variable turbulent environment. In order to improve signal reception, several mitigation techniques have been proposed and analytically investigated. This paper presents experimental results for the route diversity technique evaluations for a specific case when several diversity links intersects a common turbulent area and concurrently each passing regions with different turbulence flows

Leveraging Variational Autoencoders for Parameterized MMSE Channel Estimation

In this manuscript, we propose to utilize the generative neural network-based variational autoencoder for channel estimation. The variational autoencoder models the underlying true but unknown channel distribution as a conditional Gaussian distribution in a novel way. The derived channel estimator exploits the internal structure of the variational autoencoder to parameterize an approximation of the mean squared error optimal estimator resulting from the conditional Gaussian channel models. We provide a rigorous analysis under which conditions a variational autoencoder-based estimator is mean squared error optimal. We then present considerations that make the variational autoencoder-based estimator practical and propose three different estimator variants that differ in their access to channel knowledge during the training and evaluation phase. In particular, the proposed estimator variant trained solely on noisy pilot observations is particularly noteworthy as it does not require access to noise-free, ground-truth channel data during training or evaluation. Extensive numerical simulations first analyze the internal behavior of the variational autoencoder-based estimators and then demonstrate excellent channel estimation performance compared to related classical and machine learning-based state-of-the-art channel estimators.Comment: 13 pages, 12 figure

Joint multi-baseline SAR interferometry

We propose a technique to provide interferometry by combining multiple images of the same area. This technique differs from the multi-baseline approach in literature as (a) it exploits all the images simultaneously, (b) it performs a spectral shift preprocessing to remove most of the decorrelation, and (c) it exploits distributed targets. The technique is mainly intended for DEM generation at centimetric accuracy, as well as for differential interferometry. The problem is framed in the contest of single-input multiple-output (SIMO) channel estimation via the cross-relations (CR) technique and the resulting algorithm provides significant improvements with respect to conventional approaches based either on independent analysis of single interferograms or multi-baselines phase analysis of single pixels of current literature, for those targets that are correlated in all the images, like for long-term coherent areas, or for acquisitions taken with a short revisit time (as those gathered with future satellite constellations)