375,561 research outputs found
Position estimation from direction or range measurements
International audienceThis paper revisits the problems of estimating the position of an object moving in n (≥ 2)-dimensional Euclidean space using velocity measurements and either direction or range measurements of one or multiple source points. The proposed solutions exploit the Continuous Riccati Equation (CRE) to calculate observer gains yielding global uniform exponential stability of zero estimation errors, also when the measured velocity is biased by an unknown constant vector or when direction measurements are corrupted by an unknown constant bias. With respect to prior contributions on these subjects they provide a coherent generalization of existing solutions with the preoccupation of pointing out general and explicit persistent excitation (p.e.) conditions whose satisfaction ensures uniform exponential stability of the observers
Riccati observers for position and velocity bias estimation from either direction or range measurements
This paper revisits the problems of estimating the position of an object moving in n (≥ 2)-dimensional Euclidean space using velocity measurements and either direction or range measurements of one or multiple source points. The proposed solutions exploit the Continuous Riccati Equation (CRE) to calculate observer gains yielding global exponential stability of zero estimation errors, even in the case where the measured velocity is biased by an unknown constant perturbation. These results are obtained under persistent excitation (p.e.) conditions depending on the number of source points and body motion that ensure both uniform observability and good conditioning of the CRE solutions. With respect to prior contributions on these subjects some of the proposed solutions are entirely novel while others are adapted from existing ones with the preoccupation of stating simpler and more explicit conditions under which uniform exponential stability is achieved. A complementary contribution, related to the delicate tuning of the observers gains, is the derivation of a lower-bound of the exponential rate of convergence specified as a function of the amount of persistent excitation. Simulation results illustrate the performance of the proposed observers
Riccati observers for position and velocity bias estimation from either direction or range measurements
This paper revisits the problems of estimating the position of an object moving in n (≥ 2)-dimensional Euclidean space using velocity measurements and either direction or range measurements of one or multiple source points. The proposed solutions exploit the Continuous Riccati Equation (CRE) to calculate observer gains yielding global exponential stability of zero estimation errors, even in the case where the measured velocity is biased by an unknown constant perturbation. These results are obtained under persistent excitation (p.e.) conditions depending on the number of source points and body motion that ensure both uniform observability and good conditioning of the CRE solutions. With respect to prior contributions on these subjects some of the proposed solutions are entirely novel while others are adapted from existing ones with the preoccupation of stating simpler and more explicit conditions under which uniform exponential stability is achieved. A complementary contribution, related to the delicate tuning of the observers gains, is the derivation of a lower-bound of the exponential rate of convergence specified as a function of the amount of persistent excitation. Simulation results illustrate the performance of the proposed observers
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The influences of environmental conditions on source localisation using a single vertical array and their exploitation through ground effect inversion
The performance of microphone arrays outdoors is influenced by the environmental conditions. Numerical simulations indicate that, while horizontal arrays are hardly affected, direction-of-arrival (DOA) estimation with vertical arrays becomes biased in presence of ground reflections and sound speed gradients. Turbulence leads to a huge variability in the estimates by reducing the ground effect. Ground effect can be exploited by combining classical source localization with an appropriate propagation model (ground effect inversion). Not only does this allow the source elevation and range to be determined with a single vertical array but also it allows separation of sources which can no longer be distinguished by far field localization methods. Furthermore, simulations provide detail of the achievable spatial resolution depending on frequency range, array size and localization algorithm and show a clear advantage of broadband processing. Outdoor measurements with one or two sources confirm the results of the numerical simulations
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.
Routing Unmanned Vehicles in GPS-Denied Environments
Most of the routing algorithms for unmanned vehicles, that arise in data
gathering and monitoring applications in the literature, rely on the Global
Positioning System (GPS) information for localization. However, disruption of
GPS signals either intentionally or unintentionally could potentially render
these algorithms not applicable. In this article, we present a novel method to
address this difficulty by combining methods from cooperative localization and
routing. In particular, the article formulates a fundamental combinatorial
optimization problem to plan routes for an unmanned vehicle in a GPS-restricted
environment while enabling localization for the vehicle. We also develop
algorithms to compute optimal paths for the vehicle using the proposed
formulation. Extensive simulation results are also presented to corroborate the
effectiveness and performance of the proposed formulation and algorithms.Comment: Publised in International Conference on Umanned Aerial System
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