Title :
Improved Position Estimation Using Hybrid TW-TOA and TDOA in Cooperative Networks
Author :
Gholami, Mohammad Reza ; Gezici, Sinan ; Ström, Erik G.
Author_Institution :
Dept. of Signals & Syst., Chalmers Univ. of Technol., Göthenburg, Sweden
fDate :
7/1/2012 12:00:00 AM
Abstract :
This paper addresses the problem of positioning multiple target nodes in a cooperative wireless sensor network in the presence of unknown turn-around times. In this type of cooperative networks, two different reference sensors, namely, primary and secondary nodes, measure two-way time-of-arrival (TW-TOA) and time-difference-of-arrival (TDOA), respectively. Motivated by the role of secondary nodes, we extend the role of target nodes such that they can be considered as pseudo secondary nodes. By modeling turn-around times as nuisance parameters, we derive a maximum likelihood estimator (MLE) that poses a difficult global optimization problem due to its nonconvex objective function. To avoid drawbacks in solving the MLE, we linearize the measurements using two different techniques, namely, nonlinear processing and first-order Taylor series, and obtain linear models based on unknown parameters. The proposed linear estimator is implemented in three steps. In the first step, a coarse position estimate is obtained for each target node, and it is refined through steps two and three. To evaluate the performance of different methods, we derive the Cramér-Rao lower bound (CRLB). Simulation results show that the cooperation technique provides considerable improvements in positioning accuracy compared to the noncooperative scenario, especially for low signal-to-noise-ratios.
Keywords :
Global Positioning System; concave programming; cooperative communication; maximum likelihood estimation; time-of-arrival estimation; wireless sensor networks; CRLB; Cramér-Rao lower bound; MLE; TDOA; cooperative wireless sensor network; first-order Taylor series; global optimization problem; hybrid TW-TOA; improved position estimation; linear models; low signal-to-noise-ratios; maximum likelihood estimator; nonconvex objective function; noncooperative scenario; nonlinear processing; nuisance parameters; positioning multiple target nodes; primary nodes; pseudo secondary nodes; reference sensors; time-difference-of-arrival; turn-around times; two-way time-of-arrival; Argon; IP networks; Maximum likelihood estimation; Sensors; Time measurement; Vectors; Cooperative positioning; Cramér–Rao lower bound (CRLB); linear estimator; maximum-likelihood estimator (MLE); time-difference-of-arrival (TDOA); time-of-arrival (TOA); two-way time-of-arrival (TW-TOA); wireless sensor network;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2012.2194705