154 research outputs found
TDOA based positioning in the presence of unknown clock skew
Cataloged from PDF version of article.This paper studies the positioning problem of a
single target node based on time-difference-of-arrival (TDOA)
measurements in the presence of clock imperfections. Employing
an affine model for the behaviour of a local clock, it is observed
that TDOA based approaches suffer from a parameter of the
model, called the clock skew. Modeling the clock skew as a
nuisance parameter, this paper investigates joint clock skew and
position estimation. The maximum likelihood estimator (MLE)
is derived for this problem, which is highly nonconvex and
difficult to solve. To avoid the difficulty in solving the MLE, we
employ suitable approximations and relaxations and propose two
suboptimal estimators based on semidefinite programming and
linear estimation. To further improve the estimation accuracy,
we also propose a refining step. In addition, the Cramer-Rao ´
lower bound (CRLB) is derived for this problem as a benchmark.
Simulation results show that the proposed suboptimal estimators
can attain the CRLB for sufficiently high signal-to-noise ratios
TDOA Based Positioning in the Presence of Unknown Clock Skew
This paper studies the positioning problem of a single target node based on time-difference-of-arrival (TDOA) measurements in the presence of clock imperfections. Employing an affine model for the behaviour of a local clock, it is observed that TDOA based approaches suffer from a parameter of the model, called the clock skew. Modeling the clock skew as a nuisance parameter, this paper investigates joint clock skew and position estimation. The maximum likelihood estimator (MLE) is derived for this problem, which is highly nonconvex and difficult to solve. To avoid the difficulty in solving the MLE, we employ suitable approximations and relaxations and propose two suboptimal estimators based on semidefinite programming and linear estimation. To further improve the estimation accuracy, we also propose a refining step. In addition, the Cramér-Rao lower bound (CRLB) is derived for this problem as a benchmark. Simulation results show that the proposed suboptimal estimators can attain the CRLB for sufficiently high signal-to-noise ratios
TW-TOA based positioning in the presence of clock imperfections
This manuscript studies the positioning problem based on two-way time-of-arrival (TW-TOA) measurements in semi-asynchronous wireless sensor networks in which the clock of a target node is unsynchronized with the reference time. Since the optimal estimator for this problem involves difficult nonconvex optimization, two suboptimal estimators are proposed based on the squared-range least squares and the least absolute mean of residual errors. We formulated the former approach as an extended general trust region subproblem (EGTR) and propose a simple technique to solve it approximately. The latter approach is formulated as a difference of convex functions programming (DCP), which can be solved using a concave–convex procedure. Simulation results illustrate the high performance of the proposed techniques, especially for the DCP approach
D-SLATS: Distributed Simultaneous Localization and Time Synchronization
Through the last decade, we have witnessed a surge of Internet of Things
(IoT) devices, and with that a greater need to choreograph their actions across
both time and space. Although these two problems, namely time synchronization
and localization, share many aspects in common, they are traditionally treated
separately or combined on centralized approaches that results in an ineffcient
use of resources, or in solutions that are not scalable in terms of the number
of IoT devices. Therefore, we propose D-SLATS, a framework comprised of three
different and independent algorithms to jointly solve time synchronization and
localization problems in a distributed fashion. The First two algorithms are
based mainly on the distributed Extended Kalman Filter (EKF) whereas the third
one uses optimization techniques. No fusion center is required, and the devices
only communicate with their neighbors. The proposed methods are evaluated on
custom Ultra-Wideband communication Testbed and a quadrotor, representing a
network of both static and mobile nodes. Our algorithms achieve up to three
microseconds time synchronization accuracy and 30 cm localization error
Characterization of Multi-Carrier Locator Performance
Time-Difference-of-Arrival (TDOA) location estimation is central to an OFDM based Precision Personnel Locator system being developed at WPI. Here we describe a component of the effort towards characterizing the performance of such a system and verifying the functionality of hardware and software implementations. The performance degradations due to noise in the received signal and misalignments between transmitter and receiver clock and heterodyne frequencies are investigated. This investigation involves development of a MATLAB simulator for the entire system, experimental measures using a prototype implementation and linearized analytic analysis of specific subsystems. The three types of characterizations are compared, confirming agreement, and analytic results are used to demonstrate construction of a system engineering design tool
Distributed localization of a RF target in NLOS environments
We propose a novel distributed expectation maximization (EM) method for
non-cooperative RF device localization using a wireless sensor network. We
consider the scenario where few or no sensors receive line-of-sight signals
from the target. In the case of non-line-of-sight signals, the signal path
consists of a single reflection between the transmitter and receiver. Each
sensor is able to measure the time difference of arrival of the target's signal
with respect to a reference sensor, as well as the angle of arrival of the
target's signal. We derive a distributed EM algorithm where each node makes use
of its local information to compute summary statistics, and then shares these
statistics with its neighbors to improve its estimate of the target
localization. Since all the measurements need not be centralized at a single
location, the spectrum usage can be significantly reduced. The distributed
algorithm also allows for increased robustness of the sensor network in the
case of node failures. We show that our distributed algorithm converges, and
simulation results suggest that our method achieves an accuracy close to the
centralized EM algorithm. We apply the distributed EM algorithm to a set of
experimental measurements with a network of four nodes, which confirm that the
algorithm is able to localize a RF target in a realistic non-line-of-sight
scenario.Comment: 30 pages, 11 figure
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