82 research outputs found
Spatial Identification Methods and Systems for RFID Tags
DisertaÄŤnĂ práce je zaměřena na metody a systĂ©my pro měřenĂ vzdálenosti a lokalizaci RFID tagĹŻ pracujĂcĂch v pásmu UHF. Ăšvod je vÄ›nován popisu souÄŤasnĂ©ho stavu vÄ›deckĂ©ho poznánĂ v oblasti RFID prostorovĂ© identifikace a struÄŤnĂ©mu shrnutĂ problematiky modelovánĂ a návrhu prototypĹŻ tÄ›chto systĂ©mĹŻ. Po specifikaci cĂlĹŻ disertace pokraÄŤuje práce popisem teorie modelovánĂ degenerovanĂ©ho kanálu pro RFID komunikaci. DetailnÄ› jsou rozebrány metody měřenĂ vzdálenosti a odhadu smÄ›ru pĹ™Ăchodu signálu zaloĹľenĂ© na zpracovánĂ fázovĂ© informace. Pro účely lokalizace je navrĹľeno nÄ›kolik scĂ©nářů rozmĂstÄ›nĂ antĂ©n. Modely degenerovanĂ©ho kanálu jsou simulovány v systĂ©mu MATLAB. VĂ˝znamná část tĂ©to práce je vÄ›nována konceptu softwarovÄ› definovanĂ©ho rádia (SDR) a specifikĹŻm jeho adaptace na UHF RFID, která vyuĹľitĂ běžnĂ˝ch SDR systĂ©mĹŻ znaÄŤnÄ› omezujĂ. Diskutována je zejmĂ©na problematika prĹŻniku nosnĂ© vysĂlaÄŤe do pĹ™ijĂmacĂ cesty a poĹľadavky na signál lokálnĂho oscilátoru pouĹľĂvanĂ˝ pro směšovánĂ. Prezentovány jsou tĹ™i vyvinutĂ© prototypy: experimentálnĂ dotazovaÄŤ EXIN-1, měřicĂ systĂ©m zaloĹľenĂ˝ na platformÄ› Ettus USRP a antĂ©nnĂ pĹ™epĂnacĂ matice pro emulaci SIMO systĂ©mu. ZávÄ›reÄŤná část je zaměřena na testovánĂ a zhodnocenĂ popisovanĂ˝ch lokalizaÄŤnĂch technik, zaloĹľenĂ˝ch na měřenĂ komplexnĂ pĹ™enosovĂ© funkce RFID kanálu. Popisuje ĂşzkopásmovĂ©/širokopásmovĂ© měřenĂ vzdálenosti a metody odhadu smÄ›ru signálu. Oba navrĹľenĂ© scĂ©náře rozmĂstÄ›nĂ antĂ©n jsou v závÄ›ru ověřeny lokalizaÄŤnĂm měřenĂm v reálnĂ˝ch podmĂnkách.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.
Wireless Localization Systems: Statistical Modeling and Algorithm Design
Wireless localization systems are essential for emerging applications that rely on
context-awareness, especially in civil, logistic, and security sectors. Accurate localization in indoor environments is still a challenge and triggers a fervent research
activity worldwide. The performance of such systems relies on the quality of range
measurements gathered by processing wireless signals within the sensors composing
the localization system. Such range estimates serve as observations for the target
position inference. The quality of range estimates depends on the network intrinsic
properties and signal processing techniques. Therefore, the system design and analysis call for the statistical modeling of range information and the algorithm design
for ranging, localization and tracking. The main objectives of this thesis are: (i) the
derivation of statistical models and (ii) the design of algorithms for different wire-
less localization systems, with particular regard to passive and semi-passive systems
(i.e., active radar systems, passive radar systems, and radio frequency identification
systems). Statistical models for the range information are derived, low-complexity
algorithms with soft-decision and hard-decision are proposed, and several wideband
localization systems have been analyzed. The research activity has been conducted
also within the framework of different projects in collaboration with companies and
other universities, and within a one-year-long research period at Massachusetts Institute of Technology, Cambridge, MA, USA. The analysis of system performance,
the derived models, and the proposed algorithms are validated considering different case studies in realistic scenarios and also using the results obtained under the
aforementioned projects
Passive MIMO Radar Detection
Passive multiple-input multiple-output (MIMO) radar is a sensor network comprised of multiple distributed receivers that detects and localizes targets using the emissions from multiple non-cooperative radio frequency transmitters. This dissertation advances the theory of centralized passive MIMO radar (PMR) detection by proposing two novel generalized likelihood ratio test (GLRT) detectors. The first addresses detection in PMR networks without direct-path signals. The second addresses detection in PMR networks with direct-path signals. The probability distributions of both test statistics are investigated using recent results from random matrix theory. Equivalence is established between PMR networks without direct-path signals and passive source localization (PSL) networks. Comparison of both detectors with a centralized GLRT for active MIMO radar (AMR) detection reveals that PMR may be interpreted as the link between AMR and PSL sensor networks. In particular, under high direct-path-to-noise ratio (DNR) conditions, PMR sensitivity and ambiguity approaches that of AMR. Under low-DNR conditions, PMR sensitivity and ambiguity approaches that of PSL. At intermediate DNRs, PMR sensitivity and ambiguity smoothly varies between that of AMR and PSL. In this way, PMR unifies PSL and AMR within a common theoretical framework. This result provides insight into the fundamental natures of active and passive distributed sensing
Development and Evaluation of a Multistatic Ultrawideband Random Noise Radar
This research studies the AFIT noise network (NoNET) radar node design and the feasibility in processing the bistatic channel information of a cluster of widely distributed noise radar nodes. A system characterization is used to predict theoretical localization performance metrics. Design and integration of a distributed and central signal and data processing architecture enables the Matlab®-driven signal data acquisition, digital processing and multi-sensor image fusion. Experimental evaluation of the monostatic localization performance reveals its range measurement error standard deviation is 4.8 cm with a range resolution of 87.2(±5.9) cm. The 16-channel multistatic solution results in a 2-dimensional localization error of 7.7(±3.1) cm and a comparative analysis is performed against the netted monostatic solution. Results show that active sensing with a low probability of intercept (LPI) multistatic radar, like the NoNET, is capable of producing sub-meter accuracy and near meter-resolution imagery
Location and Map Awareness Technologies in Next Wireless Networks
In a future perspective, the need of mapping an unknown indoor environment, of localizing and retrieving information from objects with zero costs and efforts could be satisfied by the adoption of next 5G technologies. Thanks to the mix of mmW and massive arrays technologies, it will be possible to achieve a higher indoor localization accuracy without relying on a dedicated infrastructure for localization but exploiting that designed for communication purposes. Besides users localization and navigation objectives, mapping and thus, the capability of reconstructing indoor scenarios, will be an important field of research with the possibility of sharing environmental information via crowd-sourcing mechanisms between users. Finally, in the Internet of Things vision, it is expected that people, objects and devices will be interconnected to each other with the possibility of exchanging the acquired and estimated data including those regarding objects identification, positioning and mapping contents. To this end, the merge of RFID, WSN and UWB technologies has demonstrated to be a promising solution. Stimulated by this framework, this work describes different technological and signal processing approaches to ameliorate the localization capabilities and the user awareness about the environment. From one side, it has been focused on the study of the localization and mapping capabilities of multi-antenna systems based on 5G technologies considering different technological issues, as for example those related to the existing available massive arrays. From the other side, UWB-RFID systems relying on passive communication schemes have been investigated in terms of localization coverage and by developing different techniques to improve the accuracy even in presence of NLOS conditions
Multi-Sensor Data Fusion between Radio Tomographic Imaging and Noise Radar
The lack of situational awareness within an operational environment is a problem that carries high risk and expensive consequences. Radio Tomographic Imaging (RTI) and noise radar are two proven technologies capable of through-wall imaging and foliage penetration. The intent of this thesis is to provide a proof of concept for the fusion of data from RTI and noise radar. The output of this thesis will consist of a performance comparison between the two technologies followed by the derivation of a fusion technique to produce a single image. Proposals have been made for the integration of multiple-input multiple-output (MIMO) radar with RTI, however, no research has been done. Data fusion between RTI and noise radar has not been explored in academia. The impact of the expected results will provide the RTI and noise radar community a proof of concept for the fusion of data from two disparate sensor technologies. RTI is a tenured field of study at Air Force Institute of Technology (AFIT), whose results can be used to produce a platform for further options to be considered for military surveillance applications. The novelty of fusing data from RTI and noise radar is achieved with the derivation of a fusion technique utilizing Tikhonov regularization. Analyzing the results of the Tikhonov influenced techniques reveals up to a 100% error decrease in target pixel location, a 75% error decrease in target centroid location, a 28% size decrease in target pixel dispersion and a 72% improvement in an ideal solution comparison. The results of the research prove that Multi-Sensor Data Fusion (MSDF) images are of greater quality than that of the images generated by the disparate sensors independently. This effectively provides the RTI and noise radar communities a proof of concept for the fusion of data from two disparate sensor technologies
Detection and accurate localization of harmonic chipless tags
We investigate the detection and localization properties of harmonic tags working at microwave frequencies. A two-tone interrogation signal and a dedicated signal processing scheme at the receiver are proposed to eliminate phase ambiguities caused by the short signal wavelength and to provide accurate distance/position estimation even in the presence of clutter and multipath. The theoretical limits on tag detection and localization accuracy are investigated starting from a concise characterization of harmonic backscattered signals. Numerical results show that accuracies in the order of centimeters are feasible within an operational range of a few meters in the RFID UHF band
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