Modeling and optimizing positional accuracy based on hyperbolic geometry for the adaptive radio interferometric positioning system

  • Authors:

  • Hao-Ji Wu;Ho-Lin Chang;Chuang-Wen You;Hao-Hua Chu;Polly Huang

  • Affiliations:

  • Department of Computer Science and Information Engineering, National Taiwan University;Department of Computer Science and Information Engineering, National Taiwan University;Department of Computer Science and Information Engineering, National Taiwan University;Department of Computer Science and Information Engineering, National Taiwan University and Graduate Institute of Networking and Multimedia;Graduate Institute of Networking and Multimedia and Department of Electrical Engineering, National Taiwan University

  • Venue:
  • LoCA'07 Proceedings of the 3rd international conference on Location-and context-awareness
  • Year:
  • 2007

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Abstract

One of the most important performance objectives for a localization system is positional accuracy. It is fundamental and essential to general location-aware services. The radio interferometric positioning (RIP) method [1] is an exciting approach which promises sub-meter positional accuracy. In this work, we would like to enhance the RIP method by dynamically selecting the optimal anchor nodes as beacon senders to further optimizing the positional accuracy when tracking targets. We have developed an estimation error model to predict positional error of the RIP algorithm given different combinations of beacon senders. Building upon this estimation error model, we further devise an adaptive RIP method that selects the optimal sender-pair combination (SPC) according to the locations of targets relative to anchor nodes. We have implemented the adaptive RIP method and conducted experiments in a real sensor network testbed. Experimental results have shown that our adaptive RIP method outperforms the static RIP method in both single-target and multi-target tracking, and improves the average positional accuracy by 47%-60% and reduces the 90% percentile error by 55%-61%.