The Community for Technology Leaders
Green Image
Issue No. 09 - Sept. (2013 vol. 12)
ISSN: 1536-1233
pp: 1801-1813
Mark Hedley , CSIRO, Marsfield
Thuraiappah Sathyan , University of Adelaide, Adelaide
ABSTRACT
The utility of wireless networks for many applications is increased if the locations of the nodes in the network can be tracked based on the measurements between communicating nodes. Many applications, such as tracking fire fighters in large buildings, require the deployment of mobile ad hoc networks. Real-time tracking in such environments is a challenging task, particularly combined with restrictions on computational and communication resources in mobile devices. In this paper, we present a new algorithm using the Bayesian framework for cooperative tracking of nodes, which allows accurate tracking over large areas using only a small number of anchor nodes. The proposed algorithm requires lower computational and communication resources than existing algorithms. Simulation results show that the algorithm performs well with the tracking error being close to the posterior Cramér-Rao lower bound that we derive for cooperative tracking. Experimental results for a network deployed in an indoor office environment with external global position system-referenced anchor nodes are presented. A computationally simple indoor range error model for measurements at the 5.8-GHz ISM band that yields positioning accuracy close to that obtained when using the actual range error distribution is also presented.
INDEX TERMS
Mobile communication, Signal processing algorithms, Mobile computing, Wireless networks, Time measurement, Prediction algorithms, State estimation, range error model, Wireless indoor tracking, cooperative tracking, filtering algorithms, posterior Cramér Rao lower bound, time-of-arrival ranging
CITATION
Mark Hedley, Thuraiappah Sathyan, "Fast and Accurate Cooperative Tracking in Wireless Networks", IEEE Transactions on Mobile Computing, vol. 12, no. , pp. 1801-1813, Sept. 2013, doi:10.1109/TMC.2012.151
104 ms
(Ver )