A generic performance bound for node localization of wireless sensor networks

Ren-jian Feng; Jiang-wen Wan; Ning Yu; Wan-xing Ma

doi:10.1117/12.806836

13 October 2008 A generic performance bound for node localization of wireless sensor networks

Ren-jian Feng, Jiang-wen Wan, Ning Yu, Wan-xing Ma

Proceedings Volume 7127, Seventh International Symposium on Instrumentation and Control Technology: Sensors and Instruments, Computer Simulation, and Artificial Intelligence; 71272P (2008) https://doi.org/10.1117/12.806836
Event: Seventh International Symposium on Instrumentation and Control Technology, 2008, Beijing, China

Abstract

An effective evaluation criterion is necessary to investigate the performance of a localization algorithm for wireless sensor networks. The Cramer-Rao Bound (CRB) is the lower bound of the localization error and can be applied as a performance evaluation criterion of a localization algorithm. The CRB on estimation accuracy for both range-based and range-free localization is studied. The CRB for range-based localization, which is suitable for different measurement methods, is derived on the basis of Gaussian noise model. For the range-free localization, the condition of CRB and the error distribution of the estimated distance which is computed by the average hop size and hop counter between nodes are analyzed. The result reveals that the condition is satisfied when the node location is calculated by the estimated distances. Subsequently the CRB for range-free localization is acquired. The localization accuracy of three typical algorithms, AHLos, DV-distance and DV-hop, are analyzed by the simulation experiments. The results verify the CRBs for both range-based and range-free localizations.

Citation Download Citation

Ren-jian Feng, Jiang-wen Wan, Ning Yu, and Wan-xing Ma "A generic performance bound for node localization of wireless sensor networks", Proc. SPIE 7127, Seventh International Symposium on Instrumentation and Control Technology: Sensors and Instruments, Computer Simulation, and Artificial Intelligence, 71272P (13 October 2008); https://doi.org/10.1117/12.806836

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