Robust distributed network localization with noisy range measurements
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Distributed localization using noisy distance and angle information
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
Distributed weighted-multidimensional scaling for node localization in sensor networks
ACM Transactions on Sensor Networks (TOSN)
A Theory of Network Localization
IEEE Transactions on Mobile Computing
Relative location estimation in wireless sensor networks
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Distributing the Kalman Filter for Large-Scale Systems
IEEE Transactions on Signal Processing - Part I
Sensor Localization under Limited Measurement Capabilities
IEEE Network: The Magazine of Global Internetworking
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This paper addresses cooperative localization for mobile ad-hoc networks that benefits from the node velocity estimation. Given pair-wise range measurement and relative speed measurement between communicating nodes, the relative node positions are estimated using an extended Kalman filter. The state-space equation of the Kalman filter incorporates the node positions with their velocities. The measurement equation takes into account the log-normal distribution of the received signal power and the Gaussian distribution of the relative speed measurement error. Distributed algorithm is derived for practical use. The simulation results show the performance of the network localization with the assistance of node velocity estimation. The velocities are, however, not tracked using the Kalman filter; Separated method is proposed to estimate the node velocities.