Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Node Localization Using Mobile Robots in Delay-Tolerant Sensor Networks
IEEE Transactions on Mobile Computing
Bearings-only target localization using total least squares
Signal Processing
Optimality analysis of sensor-target localization geometries
Automatica (Journal of IFAC)
Joint synchronization and localization using TOAs: a linearization based WLS solution
IEEE Journal on Selected Areas in Communications - Special issue on simple wireless sensor networking solutions
A two-way time of flight ranging scheme for wireless sensor networks
EWSN'11 Proceedings of the 8th European conference on Wireless sensor networks
Analysis of WLAN's received signal strength indication for indoor location fingerprinting
Pervasive and Mobile Computing
Relative location estimation in wireless sensor networks
IEEE Transactions on Signal Processing
Optimal sensor placement and motion coordination for target tracking
Automatica (Journal of IFAC)
Source Localization in Wireless Sensor Networks From Signal Time-of-Arrival Measurements
IEEE Transactions on Signal Processing
Linear Least Squares Approach for Accurate Received Signal Strength Based Source Localization
IEEE Transactions on Signal Processing
Hi-index | 22.14 |
In this paper, we study the Cramer-Rao Lower Bound (CRLB) in single-hop sensor localization using measurements derived from received signal strength (RSS), time of arrival (TOA) and bearing, respectively, from a novel perspective. Differently from the existing work, we use a statistical sensor-anchor geometry modeling method, with the result that the trace of the associated CRLB matrix, as a scalar metric for performance limits of sensor localization, becomes a random variable. Given a probability measure for the sensor-anchor geometry, the statistical properties of the metric are analyzed to demonstrate properties of sensor localization. Using the Central Limit Theorems for U-statistics, we show that as the number of anchors increases, the metric is asymptotically normal in the RSS/bearing case, and converges to a random variable which is an affine transformation of a chi-square random variable of degree 2 in the TOA case. We provide formulas quantitatively describing the relationship among the mean and standard deviation of the metric, the number of the anchors, the parameters of communication channels, the noise statistics in measurements and the spatial distribution of the anchors. These formulas, though asymptotic in the number of the anchors, in many cases turn out to be remarkably accurate in predicting performance limits, even if the number is small. Simulations are carried out to confirm our results.