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논문검색

A Novel Method for Unstable-signal Sensor Localization in Smart Home Environments

초록

영어

Wireless sensor networks receive much attention in these few years due to its wide
spectrum of applications. Localization is one of the significant techniques in the ubiquitous
sensor networks, and most localization techniques nowadays apply RSSI-based ranging
techniques to compute the location of the object in wireless sensor network. However, a
wireless sensor network is of a fading-signal environment that comprises noises, and the
noises cause RSSI to become unstable and lead to abrupt distance estimates. In this paper, we
propose Verification-Based Localization Method (VBLM) to alleviate the effect of the
unstable signal and provide the high-accuracy location estimates in wireless sensor
environments. The basic idea of VBLM is to prune noisy signals in the localization process. In
our method, the sensor node would use another neighboring beacon to assist to verify the
quality of received signal under acceptable communication cost, and thus, the noisy signals
can be removed to avoid increasing the error in the localization. The experimental results
show that VBLM indeed reduces the localization error in the unstable signal sensor networks
than other localization methods.

목차

Abstract
 1. Introduction
 2. Related work
 3. Environment
 4. Verification-based localization method (VBLM)
  4.1. Signal-matching table
  4.2. Verification-based ranging algorithm (VBRA)
  4.3. Location calculation
  4.4. Interaction Analysis among Nodes
  4.5 Discussions
 5. Experiment results
  5.1. Characterizing the RSSI versus distance
  5.2. Effect of noises on distance estimations
  5.3. Effect of noises on localization
  5.4. Effect of the number of beacons
 6. Conclusions and future work
 7. Acknowledgment
 References

저자정보

  • Chao-Chun Chen Dept. of Comp. Sci. & Info. Engr. Southern Taiwan University,
  • Ding-Chau Wang Dept. of Info. Mgmt. Southern Taiwan University,
  • Yong-Ming Huang Dept. of Info. & Comm. Southern Taiwan University,

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