10 research outputs found
Vehicular Position Tracking Using LTE Signals
This paper proposes and validates, in the field, an approach for position tracking that is based on Long-Term Evolution (LTE) downlink signal measurements. A setup for real data live gathering is used to collect LTE signals while driving a car in the town of Rapperswil, Switzerland. The collected data are then processed to extract the received LTE cell-specific reference signals (CRSs), which are exploited for estimating pseudoranges. More precisely, the pseudoranges are evaluated by using the \u201cESPRIT and Kalman Filter for Time-of-Arrival Tracking\u201d (EKAT) algorithm and by taking advantage of signal combining in the time, frequency, spatial, and cell ID domains. Finally, the pseudoranges are corrected for base station's clock bias and drift, which are previously estimated, and are used in a positioning filter. The obtained results demonstrate the feasibility of a position tracking system based on the reception of LTE downlink signals
Positioning of High-speed Trains using 5G New Radio Synchronization Signals
We study positioning of high-speed trains in 5G new radio (NR) networks by
utilizing specific NR synchronization signals. The studies are based on
simulations with 3GPP-specified radio channel models including path loss,
shadowing and fast fading effects. The considered positioning approach exploits
measurement of Time-Of-Arrival (TOA) and Angle-Of-Departure (AOD), which are
estimated from beamformed NR synchronization signals. Based on the given
measurements and the assumed train movement model, the train position is
tracked by using an Extended Kalman Filter (EKF), which is able to handle the
non-linear relationship between the TOA and AOD measurements, and the estimated
train position parameters. It is shown that in the considered scenario the TOA
measurements are able to achieve better accuracy compared to the AOD
measurements. However, as shown by the results, the best tracking performance
is achieved, when both of the measurements are considered. In this case, a very
high, sub-meter, tracking accuracy can be achieved for most (>75%) of the
tracking time, thus achieving the positioning accuracy requirements envisioned
for the 5G NR. The pursued high-accuracy and high-availability positioning
technology is considered to be in a key role in several envisioned HST use
cases, such as mission-critical autonomous train systems.Comment: 6 pages, 5 figures, IEEE WCNC 2018 (Wireless Communications and
Networking Conference
SLAM using LTE Multipath Component Delays
Cellular radio based localization can be an important complement or alternative to other localization technologies, as base stations continuously transmit signals of opportunity with beneficial positioning properties. In this paper, we use the long term evolution (LTE) cell-specific reference signal for this purpose. The multipath component delays are estimated by the ESPRIT algorithm, and the estimated multipath component delays of different snapshots are associated by global nearest neighbor with a Kalman filter. Rao-Blackwellized particle filter based simultaneous localization and mapping (SLAM) is then applied to estimate the position of user equipment and that of the base station and virtual transmitters. In a measurement campaign, data from one base station was logged, and the analysis based on the data shows that, at the end of the measurement, the SLAM performance is 11 meters better than that with only inertial measurement unit (IMU)
Infrastructure Wi-Fi for connected autonomous vehicle positioning : a review of the state-of-the-art
In order to realize intelligent vehicular transport networks and self driving cars, connected autonomous vehicles (CAVs) are required to be able to estimate their position to the nearest centimeter. Traditional positioning in CAVs is realized by using a global navigation satellite system (GNSS) such as global positioning system (GPS) or by fusing weighted location parameters from a GNSS with an inertial navigation systems (INSs). In urban environments where Wi-Fi coverage is ubiquitous and GNSS signals experience signal blockage, multipath or non line-of-sight (NLOS) propagation, enterprise or carrier-grade Wi-Fi networks can be opportunistically used for localization or “fused” with GNSS to improve the localization accuracy and precision. While GNSS-free localization systems are in the literature, a survey of vehicle localization from the perspective of a Wi-Fi anchor/infrastructure is limited. Consequently, this review seeks to investigate recent technological advances relating to positioning techniques between an ego vehicle and a vehicular network infrastructure. Also discussed in this paper is an analysis of the location accuracy, complexity and applicability of surveyed literature with respect to intelligent transportation system requirements for CAVs. It is envisaged that hybrid vehicular localization systems will enable pervasive localization services for CAVs as they travel through urban canyons, dense foliage or multi-story car parks
Wiometrics: Comparative Performance of Artificial Neural Networks for Wireless Navigation
Radio signals are used broadly as navigation aids, and current and future
terrestrial wireless communication systems have properties that make their
dual-use for this purpose attractive. Sub-6 GHz carrier frequencies enable
widespread coverage for data communication and navigation, but typically offer
smaller bandwidths and limited resolution for precise estimation of geometries,
particularly in environments where propagation channels are diffuse in time
and/or space. Non-parametric methods have been employed with some success for
such scenarios both commercially and in literature, but often with an emphasis
on low-cost hardware and simple models of propagation, or with simulations that
do not fully capture hardware impairments and complex propagation mechanisms.
In this article, we make opportunistic observations of downlink signals
transmitted by commercial cellular networks by using a software-defined radio
and massive antenna array mounted on a passenger vehicle in an urban non
line-of-sight scenario, together with a ground truth reference for vehicle
pose. With these observations as inputs, we employ artificial neural networks
to generate estimates of vehicle location and heading for various artificial
neural network architectures and different representations of the input
observation data, which we call wiometrics, and compare the performance for
navigation. Position accuracy on the order of a few meters, and heading
accuracy of a few degrees, are achieved for the best-performing combinations of
networks and wiometrics. Based on the results of the experiments we draw
conclusions regarding possible future directions for wireless navigation using
statistical methods
Soft information for localization-of-things
Location awareness is vital for emerging Internetof-
Things applications and opens a new era for Localizationof-
Things. This paper first reviews the classical localization
techniques based on single-value metrics, such as range and
angle estimates, and on fixed measurement models, such as
Gaussian distributions with mean equal to the true value of the
metric. Then, it presents a new localization approach based
on soft information (SI) extracted from intra- and inter-node
measurements, as well as from contextual data. In particular,
efficient techniques for learning and fusing different kinds of SI
are described. Case studies are presented for two scenarios in
which sensing measurements are based on: 1) noisy features
and non-line-of-sight detector outputs and 2) IEEE 802.15.4a
standard. The results show that SI-based localization is highly
efficient, can significantly outperform classical techniques, and
provides robustness to harsh propagation conditions.RYC-2016-1938
Sistema de geolocalización para la atención de solicitudes de búsqueda servicios móviles. Caso aplicado en la empresa BITEL
Esta tesis abarca el desarrollo de un sistema de geolocalización, mediante la
metodología de desarrollo RUP, para la atencion de solicitudes de búsquedas de
servicios móviles en la empresa VIETTEL PERU S.A.C., la empresa antes de la
implementación de la aplicación presentaba deficiencias en cuanto a el índice de
eficacia y la disponibilidad del servicio, los cuales fueron importantes para resolver
los objetivos, incrementar el índice de eficacia y disponibilidad de servicio para la
atencion de solicitudes de localización.
Se utilizó la metodología RUP para el desarrollo de la aplicación, debido a que se
ajusta al desarrollo iterativo. La investigación es de tipo aplicada, el diseño es
experimental y el enfoque es cuantitativo. La muestra fue de 348 solicitudes de
localización. La técnica de recolección da datos fue el fichaje y el instrumento
ficha de registro. Los datos se procesaron y analizaron con el software SPSS V25.
La implementación del sistema de geolocalización permitió aumentar el índice de
eficacia de 94,32% a 99,20%, de forma similar, se consiguió incrementar la
disponibilidad del servicio de 96,39% a 99,58%. Entonces se puede concluir que
el sistema de geolocalización logró mejorar la atención de solicitudes de
búsqueda de servicios móviles
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Distributed localisation algorithm for wireless ad hoc networks of moving nodes
Existing ad hoc network localisation solutions rely either on external location references or network-wide exchange of information and centralised processing and computation of location estimates. Without these, nodes are not able to estimate the relative locations of other nodes within their communication range. This thesis defines a new distributed localisation algorithm for ad hoc networks of moving nodes. The Relative Neighbour Localisation (RNL) algorithm works without any external localisation signal or systems and does not assume centralised information processing. The idea behind the location estimates produced by the RNL algorithm is the relationship between the relative locations of two nodes, their mobility parameters and the signal strengths measured between them. The proposed algorithm makes use of the data available to each node to produce a location estimate. The signal strength each node is capable of measuring is used as one algorithm input. The other input is the velocity vector of the neighbouring node, composed of its speed and direction of movement, which each node is assumed to periodically broadcast. The relationship between the signal strength and the mobility parameters on one, and the relative location on the other side can be analytically formulated in an ideal case. The limitations of a realistic scenario complicate this relationship, making it very difficult to formulate analytically. An empirical approach is thus used. The angle and the distance estimates are individually computed, together forming a two-dimensional location estimate. The performance of the algorithm was analysed in detail using simulation, showing a median estimate error of under 10m, and its application was tested through design and evaluation of a distributed sensing coverage algorithm, showing RNL location estimates can provide 90% of the coverage achievable with true locations being known
Sensors and Systems for Indoor Positioning
This reprint is a reprint of the articles that appeared in Sensors' (MDPI) Special Issue on “Sensors and Systems for Indoor Positioning". The published original contributions focused on systems and technologies to enable indoor applications
Mobile user positioning in public land mobile networks by using methods based on support vector machines.
Tokom prethodnih godina, potreba za podrškom sve većeg broja LBS (Location
Based Services) servisa dovela je do intezivnog razvoja tehnika za pozicioniranje
mobilnih korisnika (objekata) u radio sistemima. Pri tom, zahtevi koje sistemi za
pozicioniranje treba da ispune, prvenstveno po pitanju tačnosti, ali i po pitanju
kašnjenja, dostupnosti servisa, kompleksnosti i cene implementacije, postaju sve
strožiji...Over the last years, the necessity of providing the support for various Location
Based Services (LBS) has led to the intensive development of the techniques for mobile
user (objects) positioning in radio systems. At the same time, the requirements that need
to be fulfilled by the positioning technique in terms of accuracy, latency, availability,
complexity and implementation costs, are getting higher..