185 research outputs found
Three-D multilateration: A precision geodetic measurement system
A technique of satellite geodesy for determining the relative three dimensional coordinates of ground stations within one centimeter over baselines of 20 to 10,000 kilometers is discussed. The system is referred to as 3-D Multilateration and has applications in earthquake hazard assessment, precision surveying, plate tectonics, and orbital mechanics. The accuracy is obtained by using pulsed lasers to obtain simultaneous slant ranges between several ground stations and a moving retroreflector with known trajectory for aiming the lasers
Euclidean distance geometry and applications
Euclidean distance geometry is the study of Euclidean geometry based on the
concept of distance. This is useful in several applications where the input
data consists of an incomplete set of distances, and the output is a set of
points in Euclidean space that realizes the given distances. We survey some of
the theory of Euclidean distance geometry and some of the most important
applications: molecular conformation, localization of sensor networks and
statics.Comment: 64 pages, 21 figure
A Maximum Likelihood TOA Based Estimator For Localization in Heterogeneous Networks
International audienceIn this paper, we exploit the concept of data fusion in hybrid localization systems by combining different TOA (Time of Arrival) observables coming from different RATs (Radio Access Technology) and characterized by different precisions in order to enhance the positioning accuracy. A new Maximum Likelihood estimator is developed to fuse different measured ranges with different variances. In order to evaluate this estimator, Monte Carlo simulations are carried out in a generic environment and Cramer Rao Lower Bounds (CRLB) are investigated. This algorithm shows enhanced positioning accuracy at reasonable noise levels comparing to the typical Weighted Least Square estimator. The CRLB reveals that the choice of the number, and the configuration of Anchor nodes, and the type of RAT may enhance positioning accuracy
A two phase framework for visible light-based positioning in an indoor environment: performance, latency, and illumination
Recently with the advancement of solid state lighting and the application thereof
to Visible Light Communications (VLC), the concept of Visible Light Positioning
(VLP) has been targeted as a very attractive indoor positioning system (IPS) due to
its ubiquity, directionality, spatial reuse, and relatively high modulation bandwidth.
IPSs, in general, have 4 major components (1) a modulation, (2) a multiple access
scheme, (3) a channel measurement, and (4) a positioning algorithm. A number of
VLP approaches have been proposed in the literature and primarily focus on a fixed
combination of these elements and moreover evaluate the quality of the contribution
often by accuracy or precision alone.
In this dissertation, we provide a novel two-phase indoor positioning algorithmic
framework that is able to increase robustness when subject to insufficient anchor luminaries
and also incorporate any combination of the four major IPS components.
The first phase provides robust and timely albeit less accurate positioning proximity
estimates without requiring more than a single luminary anchor using time division
access to On Off Keying (OOK) modulated signals while the second phase provides a
more accurate, conventional, positioning estimate approach using a novel geometric
constrained triangulation algorithm based on angle of arrival (AoA) measurements.
However, this approach is still an application of a specific combination of IPS components.
To achieve a broader impact, the framework is employed on a collection
of IPS component combinations ranging from (1) pulsed modulations to multicarrier
modulations, (2) time, frequency, and code division multiple access, (3) received signal
strength (RSS), time of flight (ToF), and AoA, as well as (4) trilateration and
triangulation positioning algorithms.
Results illustrate full room positioning coverage ranging with median accuracies
ranging from 3.09 cm to 12.07 cm at 50% duty cycle illumination levels. The framework
further allows for duty cycle variation to include dimming modulations and results
range from 3.62 cm to 13.15 cm at 20% duty cycle while 2.06 cm to 8.44 cm at a
78% duty cycle. Testbed results reinforce this frameworks applicability. Lastly, a
novel latency constrained optimization algorithm can be overlaid on the two phase
framework to decide when to simply use the coarse estimate or when to expend more
computational resources on a potentially more accurate fine estimate.
The creation of the two phase framework enables robust, illumination, latency
sensitive positioning with the ability to be applied within a vast array of system
deployment constraints
Mobile Location with NLOS Identification and Mitigation Based on Modified Kalman Filtering
In order to enhance accuracy and reliability of wireless location in the mixed line-of-sight (LOS) and non-line-of-sight (NLOS) environments, a robust mobile location algorithm is presented to track the position of a mobile node (MN). An extended Kalman filter (EKF) modified in the updating phase is utilized to reduce the NLOS error in rough wireless environments, in which the NLOS bias contained in each measurement range is estimated directly by the constrained optimization method. To identify the change of channel situation between NLOS and LOS, a low complexity identification method based on innovation vectors is proposed. Numerical results illustrate that the location errors of the proposed algorithm are all significantly smaller than those of the iterated NLOS EKF algorithm and the conventional EKF algorithm in different LOS/NLOS conditions. Moreover, this location method does not require any statistical distribution knowledge of the NLOS error. In addition, complexity experiments suggest that this algorithm supports real-time applications
The IceCube Neutrino Observatory: Instrumentation and Online Systems
The IceCube Neutrino Observatory is a cubic-kilometer-scale high-energy
neutrino detector built into the ice at the South Pole. Construction of
IceCube, the largest neutrino detector built to date, was completed in 2011 and
enabled the discovery of high-energy astrophysical neutrinos. We describe here
the design, production, and calibration of the IceCube digital optical module
(DOM), the cable systems, computing hardware, and our methodology for drilling
and deployment. We also describe the online triggering and data filtering
systems that select candidate neutrino and cosmic ray events for analysis. Due
to a rigorous pre-deployment protocol, 98.4% of the DOMs in the deep ice are
operating and collecting data. IceCube routinely achieves a detector uptime of
99% by emphasizing software stability and monitoring. Detector operations have
been stable since construction was completed, and the detector is expected to
operate at least until the end of the next decade.Comment: 83 pages, 50 figures; updated with minor changes from journal review
and proofin
Indoor and outdoor localization for AGVs in the primary aluminum industry
The goal of this project is to analyze two types of AGV indoor and outdoor localization techniques in an aluminum smelter building with a particular operative vehicle. The indoor localization is performed with the ARTag markers system while the outdoor localization employs multiple Wi-Fi transceivers to trilaterate the position of the vehicle based on the RSSI value. Finally, raw estimated pose is fused with the IMU sensor data using the extended kalman filter to increase localization accuracy.openEmbargo tempraneo per motivi di segretezza e/o di proprietĂ dei risultati e informazioni di enti esterni o aziende private che hanno partecipato alla realizzazione del lavoro di ricerca relativo alla tes
Sensing and Signal Processing in Smart Healthcare
In the last decade, we have witnessed the rapid development of electronic technologies that are transforming our daily lives. Such technologies are often integrated with various sensors that facilitate the collection of human motion and physiological data and are equipped with wireless communication modules such as Bluetooth, radio frequency identification, and near-field communication. In smart healthcare applications, designing ergonomic and intuitive human–computer interfaces is crucial because a system that is not easy to use will create a huge obstacle to adoption and may significantly reduce the efficacy of the solution. Signal and data processing is another important consideration in smart healthcare applications because it must ensure high accuracy with a high level of confidence in order for the applications to be useful for clinicians in making diagnosis and treatment decisions. This Special Issue is a collection of 10 articles selected from a total of 26 contributions. These contributions span the areas of signal processing and smart healthcare systems mostly contributed by authors from Europe, including Italy, Spain, France, Portugal, Romania, Sweden, and Netherlands. Authors from China, Korea, Taiwan, Indonesia, and Ecuador are also included
Towards the Next Generation of Location-Aware Communications
This thesis is motivated by the expected implementation of the
next generation mobile networks (5G) from 2020, which is being
designed with a radical paradigm shift towards millimeter-wave
technology (mmWave). Operating in 30--300 GHz frequency band
(1--10 mm wavelengths), massive antenna arrays that provide a
high angular resolution, while being packed on a small area will
be used. Moreover, since the abundant mmWave spectrum is barely
occupied, large bandwidth allocation is possible and will enable
low-error time estimation. With this high spatiotemporal
resolution, mmWave technology readily lends itself to extremely
accurate localization that can be harnessed in the network design
and optimization, as well as utilized in many modern
applications. Localization in 5G is still in early stages, and
very little is known about its performance and feasibility.
In this thesis, we contribute to the understanding of 5G mmWave
localization by focusing on challenges pertaining to this
emerging technology. Towards that, we start by considering a
conventional cellular system and propose a positioning method
under outdoor LOS/NLOS conditions that, although approaches the
Cram\'er-Rao lower bound (CRLB), provides accuracy in the order
of meters. This shows that conventional systems have limited
range of location-aware applications. Next, we focus on mmWave
localization in three stages. Firstly, we tackle the initial
access (IA) problem, whereby user equipment (UE) attempts to
establish a link with a base station (BS). The challenge in this
problem stems from the high directivity of mmWave. We investigate
two beamforming schemes: directional and random. Subsequently, we
address 3D localization beyond IA phase. Devices nowadays have
higher computational capabilities and may perform localization in
the downlink. However, beamforming on the UE side is sensitive to
the device orientation. Thus, we study localization in both the
uplink and downlink under multipath propagation and derive the
position (PEB) and orientation error bounds (OEB). We also
investigate the impact of the number of antennas and the number
of beams on these bounds. Finally, the above components assume
that the system is synchronized. However, synchronization in
communication systems is not usually tight enough for
localization. Therefore, we study two-way localization as a means
to alleviate the synchronization requirement and investigate two
protocols: distributed (DLP) and centralized (CLP).
Our results show that random-phase beamforming is more
appropriate IA approach in the studied scenarios. We also observe
that the uplink and downlink are not equivalent, in that the
error bounds scale differently with the number of antennas, and
that uplink localization is sensitive to the UE orientation,
while downlink is not. Furthermore, we find that NLOS paths
generally boost localization. The investigation of the two-way
protocols shows that CLP outperforms DLP by a significant margin.
We also observe that mmWave localization is mainly limited by
angular rather than temporal estimation.
In conclusion, we show that mmWave systems are capable of
localizing a UE with sub-meter position error, and sub-degree
orientation error, which asserts that mmWave will play a central
role in communication network optimization and unlock
opportunities that were not available in the previous generation
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