Journal ArticleDOI
Linear Least Squares Approach for Accurate Received Signal Strength Based Source Localization
Hing Cheung So,Lanxin Lin +1 more
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TLDR
It is proved that the performance of the improved LLS estimator achieves Cramer-Rao lower bound at sufficiently small noise conditions and the variances of the position estimates are derived and confirmed by computer simulations.Abstract:
A conventional approach for passive source localization is to utilize signal strength measurements of the emitted source received at an array of spatially separated sensors. The received signal strength (RSS) information can be converted to distance estimates for constructing a set of circular equations, from which the target position is determined. Nevertheless, a major challenge in this approach lies in the shadow fading effect which corresponds to multiplicative measurement errors. By utilizing the mean and variance of the squared distance estimates, we devise two linear least squares (LLS) estimators for RSS-based positioning in this paper. The first one is a best linear unbiased estimator while the second is its improved version by exploiting the known relation between the parameter estimates. The variances of the position estimates are derived and confirmed by computer simulations. In particular, it is proved that the performance of the improved LLS estimator achieves Cramer-Rao lower bound at sufficiently small noise conditions.read more
Citations
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Journal ArticleDOI
Cooperative Received Signal Strength-Based Sensor Localization With Unknown Transmit Powers
TL;DR: A novel semidefinite programming (SDP) relaxation technique is derived by converting the ML minimization problem into a convex problem which can be solved efficiently and requires only an estimate of the path loss exponent (PLE).
Journal ArticleDOI
On Received-Signal-Strength Based Localization with Unknown Transmit Power and Path Loss Exponent
TL;DR: This letter derives a weighed least squares (WLS) formulation to jointly estimate the sensor node location and the transmit power, based on the unscented transformation (UT) for the case of unknown transmit power and unknown PLE.
Book ChapterDOI
Source Localization: Algorithms and Analysis
Reza Zekavat,R. Michael Buehrer +1 more
TL;DR: This chapter contains sections titled: Introduction Measurement Models and Principles for source Localization Algorithms for Source Localization Performance Analysis for LocalizationAlgorithms and Conclusion.
Journal ArticleDOI
Multiple Source Localization in Wireless Sensor Networks Based on Time of Arrival Measurement
TL;DR: This work considers simultaneous estimation of source-measurement associations and the source locations, in addition to finding the initial signal transmission time and proposes an efficient three-step algorithm that progressively simplifies the original problem through convex relaxation and sensible approximations.
Journal ArticleDOI
BLE Beacons for Indoor Positioning at an Interactive IoT-Based Smart Museum
TL;DR: Experimental results on distance estimation, location, and detection accuracy show that BLE beacon is a promising solution for an interactive smart museum.
References
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Journal ArticleDOI
A multidimensional scaling framework for mobile location using time-of-arrival measurements
Kwok-Wai Cheung,Hing Cheung So +1 more
TL;DR: A simple algorithm is devised using time-of-arrival measurements of the signal from the mobile station received at three or more base stations, via modifying the classical multidimensional scaling technique, which has been developed for analyzing data obtained from physical, biological, and behavioral science.
Proceedings ArticleDOI
Positioning Algorithms for Cellular Networks Using TDOA
Christian Mensing,Simon Plass +1 more
TL;DR: The Levenberg-Marquardt algorithm is applied as a new approach in the cellular network localization framework and it is shown that this method meets the best trade-off between accuracy and computational complexity.
Journal ArticleDOI
Automatic vehicle location in cellular communications systems
TL;DR: In this article, the authors present a method of automatic vehicle location (AVL) based on the assumption that the base stations are separated from each other by 5 km and the point-to-area terrain configuration has a 3 dB standard deviation of a normal signal strength distribution.
Journal ArticleDOI
Distance Estimation From Received Signal Strength Under Log-Normal Shadowing: Bias and Variance
TL;DR: It is shown that the underlying estimation problem is inefficient and that the maximum likelihood estimate yields a bias and a mean-square error (MSE) that both increase exponentially with the noise power.
Journal ArticleDOI
A Semidefinite Programming Approach to Source Localization in Wireless Sensor Networks
TL;DR: A novel approach to the source localization and tracking problem in wireless sensor networks is proposed by applying minimax approximation and semidefinite relaxation to transform the traditionally nonlinear and nonconvex problem into convex optimization problems for two different source localization models involving measured distance and received signal strength.