Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Wireless sensor network survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Sensor grid applications in patient monitoring
Future Generation Computer Systems
Joint time synchronization and localization of an unknown node in wireless sensor networks
IEEE Transactions on Signal Processing
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 survey of communication/networking in Smart Grids
Future Generation Computer Systems
Robust Time-Based Localization for Asynchronous Networks
IEEE Transactions on Signal Processing
Hi-index | 0.00 |
This paper considers the joint node synchronization and localization problem, a key enabling aspect for wireless sensor networks. A new algorithm that can jointly estimate the clock bias and the position of an unknown sensor node is developed. The newly proposed method only involves the applications of closed-form weighted least squares (WLS) technique and therefore has lower computational complexity than conventional maximum likelihood (ML) estimators. More importantly, through theoretical performance analysis, the new algorithm is shown to be able to achieve the Cramer-Rao Lower Bound (CRLB) accuracy under the condition of high signal-to-noise ratio (SNR), a prominent advantage over other existing closed-form methods. Simulations demonstrate the good performance of the developed algorithm.