Browsing by Keywords "Time-of-arrival"
Now showing items 1-10 of 10
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A distributed positioning algorithm for cooperative active and passive sensors
(IEEE, 2010)The problem of positioning a target node is studied for wireless sensor networks with cooperative active and passive sensors. Two-way time-of-arrival and time-difference-of-arrival measurements made by both active and ... -
Enhanced position estimation via node cooperation
(IEEE, 2010)Two-way time-of-arrival (TW-ToA) is a widely used ranging protocol that can provide the distance between two devices without time synchronization. One drawback of the TW-ToA is poor positioning accuracy in the absence of ... -
Fundamental limits and improved algorithms for linear least-squares wireless position estimation
(John Wiley & Sons, 2010-09-22)In this paper, theoretical lower bounds on performance of linear least-squares (LLS) position estimators are obtained, and performance differences between LLS and nonlinear least-squares (NLS) position estimators are ... -
Hybrid TW-TOA/TDOA positioning algorithms for cooperative wireless networks
(IEEE, 2011)The problem of positioning an unknown target is studied for a cooperative wireless sensor network using hybrid two-way time-of-arrival and time-difference-of-arrival measurements. A maximum likelihood estimator (MLE) can ... -
Improved position estimation using hybrid TW-TOA and TDOA in cooperative networks
(Institute of Electrical and Electronics Engineers, 2012-04-13)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 ... -
Positioning algorithms for cooperative networks in the presence of an unknown turn-around time
(IEEE, 2011)This paper addresses the problem of single node positioning in cooperative network using hybrid two-way time-of-arrival and time-difference-of-arrival where, the turn-around time at the target node is unknown. Considering ... -
Statistics of the MLE and Approximate Upper and Lower Bounds-Part 1: Application to TOA Estimation
(IEEE, 2014-08)In nonlinear deterministic parameter estimation, the maximum likelihood estimator (MLE) is unable to attain the Cramer-Rao lower bound at low and medium signal-to-noise ratios (SNR) due the threshold and ambiguity phenomena. ... -
Statistics of the MLE and Approximate Upper and Lower Bounds-Part 2: Threshold Computation and Optimal Signal Design
(2014)Threshold and ambiguity phenomena are studied in Part I of this paper where approximations for the mean-squared error (MSE) of the maximum-likelihood estimator are proposed using the method of interval estimation (MIE), ... -
Statistics of the MLE and approximate upper and lower bounds-Part I: Application to TOA estimation
(Institute of Electrical and Electronics Engineers Inc., 2014)In nonlinear deterministic parameter estimation, the maximum likelihood estimator (MLE) is unable to attain the Cramér-Rao lower bound at low and medium signal-to-noise ratios (SNRs) due the threshold and ambiguity phenomena. ... -
Statistics of the MLE and approximate upper and lower bounds-part II: Threshold computation and optimal pulse design for TOA estimation
(Institute of Electrical and Electronics Engineers Inc., 2014)Threshold and ambiguity phenomena are studied in Part I of this paper where approximations for the mean-squared error (MSE) of the maximum-likelihood estimator are proposed using the method of interval estimation (MIE), ...
