757 research outputs found
Source localization and denoising: a perspective from the TDOA space
In this manuscript, we formulate the problem of denoising Time Differences of
Arrival (TDOAs) in the TDOA space, i.e. the Euclidean space spanned by TDOA
measurements. The method consists of pre-processing the TDOAs with the purpose
of reducing the measurement noise. The complete set of TDOAs (i.e., TDOAs
computed at all microphone pairs) is known to form a redundant set, which lies
on a linear subspace in the TDOA space. Noise, however, prevents TDOAs from
lying exactly on this subspace. We therefore show that TDOA denoising can be
seen as a projection operation that suppresses the component of the noise that
is orthogonal to that linear subspace. We then generalize the projection
operator also to the cases where the set of TDOAs is incomplete. We
analytically show that this operator improves the localization accuracy, and we
further confirm that via simulation.Comment: 25 pages, 9 figure
Space-Time diversity for NLOS mitigation in TDOA-based positioning systems
This paper studies the potential impact of using space-Time information in the mitigation of the Non-LineOf-Sight condition in mobile subscriber's positioning systems. First of all, this work discusses the positioning problem based on measures of Time Differences Of Arrival departing from a more exact characterization of the signal statistics and including some geometrical restrictions to achieve an improved accurate. Furthermore, a novel approach that integrates signal propagation characteristics to information provided by a suitable timing estimation model based on Cramer Rao Bound for a Rayleigh-fading channel, when antenna arrays are used at the receiver and when a set ofchannel vector estimates are available, has been introduced to study the positive benefits of space-Time diversity. These approaches are evaluated within a realistic simulation scenario.Peer ReviewedPostprint (published version
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Development and Demonstration of a TDOA-Based GNSS Interference Signal Localization System
Background theory, a reference design, and demonstration
results are given for a Global Navigation Satellite
System (GNSS) interference localization system comprising a
distributed radio-frequency sensor network that simultaneously
locates multiple interference sources by measuring their signals’
time difference of arrival (TDOA) between pairs of nodes in
the network. The end-to-end solution offered here draws from
previous work in single-emitter group delay estimation, very long
baseline interferometry, subspace-based estimation, radar, and
passive geolocation. Synchronization and automatic localization
of sensor nodes is achieved through a tightly-coupled receiver
architecture that enables phase-coherent and synchronous sampling
of the interference signals and so-called reference signals
which carry timing and positioning information. Signal and crosscorrelation
models are developed and implemented in a simulator.
Multiple-emitter subspace-based TDOA estimation techniques
are developed as well as emitter identification and localization
algorithms. Simulator performance is compared to the CramérRao
lower bound for single-emitter TDOA precision. Results are
given for a test exercise in which the system accurately locates
emitters broadcasting in the amateur radio band in Austin, TX.Aerospace Engineering and Engineering Mechanic
The significance of passive acoustic array-configurations on sperm whale range estimation when using the hyperbolic algorithm
In cetacean monitoring for population estimation, behavioural studies or mitigation,
traditional visual observations are being augmented by the use of Passive Acoustic
Monitoring (PAM) techniques that use the creature’s vocalisations for localisation.
The design of hydrophone configurations is evaluated for sperm whale (Physeter
macrocephalus) range estimation to meet the requirements of the current mitigation
regulations for a safety zone and behaviour research.
This thesis uses the Time Difference of Arrival (TDOA) of cetacean vocalisations with a
three-dimensional hyperbolic localisation algorithm. A MATLAB simulator has been
developed to model array-configurations and to assess their performance in source
range estimation for both homogeneous and non-homogeneous sound speed profiles
(SSP). The non-homogeneous medium is modelled on a Bellhop ray trace model, using
data collected from the Gulf of Mexico. The sperm whale clicks are chosen as an
exemplar of a distinctive underwater sound.
The simulator is tested with a separate synthetic source generator which produced a set
of TDOAs from a known source location. The performance in source range estimation
for Square, Trapezium, Triangular, Shifted-pair and Y-shape geometries is tested. The
Y-shape geometry, with four elements and aperture-length of 120m, is the most
accurate, giving an error of ±10m over slant ranges of 500m in a homogeneous medium,
and 300m in a non-homogeneous medium. However, for towed array deployments, the
Y-shape array is sensitive to angle-positioning-error when the geometry is seriously
distorted. The Shifted-pair geometry overcomes these limits, performing an initial
accuracy of ±30m when the vessel either moves in a straight line or turns to port or
starboard. It constitutes a recommendable array-configuration for towed array
deployments.
The thesis demonstrates that the number of receivers, the array-geometry and the arrayaperture
are important parameters to consider when designing and deploying a
hydrophone array. It is shown that certain array-configurations can significantly
improve the accuracy of source range estimation. Recommendations are made
concerning preferred array-configurations for use with PAM systems
Passive round-trip-time positioning in dense ieee 802.11 networks
The search for a unique and globally available location solution has attracted researchers for a long time. However, a solution for indoor scenarios, where high accuracy is needed, and Global Positioning System (GPS) is not available, has not been found yet. Despite the number of proposals in the literature, some require too long a calibration time for constructing the fingerprinting map, some rely on the periodic broadcast of positioning information that may downgrade the data communication channel, while others require specific hardware components that are not expected to be carried on commercial off-the-shelf (COTS) wireless devices. The scalability of the location solution is another key parameter for next-generation internet of things (IoT) and 5G scenarios. A passive solution for indoor positioning of WiFi devices is first introduced here, which merges a time-difference of arrival (TDOA) algorithm with the novel fine time measurements (FTM) introduced in IEEE 802.11mc. A proof of concept of the WiFi passive TDOA algorithm is detailed in this paper, together with a thorough discussion on the requirements of the proposed algorithmThis work was funded by the Spanish Government and European Regional Development Fund (ERDF) through Comisión Interministerial de Ciencia y TecnologÃa (CICYT) under Project PGC2018-099945-B-I00.Peer ReviewedPostprint (published version
Navigation with Limited Prior Information Using Time Difference of Arrival Measurements from Signals of Opportunity
The Global Positioning System (GPS) provides world-wide availability to high-accuracy navigation and positioning information. However, the threats to GPS are increasing, and many limitations of GPS are being encountered. Simultaneously, systems previously considered as viable backups or supplements to GPS are being shut down. This creates the need for system alternatives. Navigation using signals of opportunity (SoOP) exploits any signal that is available in a given area, regardless of whether or not the original intent of the signal was for navigation. Common techniques to compute a position estimate using SoOP include received signal strength, angle of arrival, time of arrival, and time difference of arrival (TDOA). To estimate the position of a SoOP receiver, existing TDOA algorithms require one reference receiver and multiple transmitters, all with precisely known positions. This thesis considers modifications to an existing algorithm to produce a comparable position estimate without requiring precise a priori knowledge of the transmitters or reference receiver(s). Using Amplitude Modulation (AM) SoOP, the effect of erroneous a priori data on the existing algorithm are investigated. A proof-of-concept for three new estimation algorithms is presented in this research. Two of the estimators successfully demonstrate comparable performance to the existing algorithm. This is demonstrated in six different transmitter environments using four different receiver configurations
FDOA-based passive source localization: a geometric perspective
2018 Fall.Includes bibliographical references.We consider the problem of passively locating the source of a radio-frequency signal using observations by several sensors. Received signals can be compared to obtain time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements. The geometric relationship satisfied by these measurements allow us to make inferences about the emitter's location. In this research, we choose to focus on the FDOA-based source localization problem. This problem has been less widely studied and is more difficult than solving for an emitter's location using TDOA measurements. When the FDOA-based source localization problem is formulated as a system of polynomials, the source's position is contained in the corresponding algebraic variety. This provides motivation for the use of methods from algebraic geometry, specifically numerical algebraic geometry (NAG), to solve for the emitter's location and gain insight into this system's interesting structure
A comprehensive analysis of the geometry of TDOA maps in localisation problems
In this manuscript we consider the well-established problem of TDOA-based
source localization and propose a comprehensive analysis of its solutions for
arbitrary sensor measurements and placements. More specifically, we define the
TDOA map from the physical space of source locations to the space of range
measurements (TDOAs), in the specific case of three receivers in 2D space. We
then study the identifiability of the model, giving a complete analytical
characterization of the image of this map and its invertibility. This analysis
has been conducted in a completely mathematical fashion, using many different
tools which make it valid for every sensor configuration. These results are the
first step towards the solution of more general problems involving, for
example, a larger number of sensors, uncertainty in their placement, or lack of
synchronization.Comment: 51 pages (3 appendices of 12 pages), 12 figure
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