Fine-grained localization for multiple transceiver-free objects by using RF-based technologies

Dian ZHANG, Kezhong LU, Rui MAO, Yuhong FENG, Yunhuai LIU, Zhong MING, Lionel M. NI

Research output: Journal PublicationsJournal Article (refereed)peer-review

66 Citations (Scopus)


In traditional radio-based localization methods, the target object has to carry a transmitter (e.g., active RFID), a receiver (e.g., 802.11 × detector), or a transceiver (e.g., sensor node). However, in some applications, such as safe guard systems, it is not possible to meet this precondition. In this paper, we propose a model of signal dynamics to allow the tracking of a transceiver-free object. Based on radio signal strength indicator (RSSI), which is readily available in wireless communication, three centralized tracking algorithms, and one distributed tracking algorithm are proposed to eliminate noise behaviors and improve accuracy. The midpoint and intersection algorithms can be applied to track a single object without calibration, while the best-cover algorithm has higher tracking accuracy but requires calibration. The probabilistic cover algorithm is based on distributed dynamic clustering. It can dramatically improve the localization accuracy when multiple objects are present. Our experimental test-bed is a grid sensor array based on MICA2 sensor nodes. The experimental results show that the localization accuracy for single object can reach about 0.8 m and for multiple objects is about 1 m.
Original languageEnglish
Pages (from-to)1464-1475
Number of pages12
JournalIEEE Transactions on Parallel and Distributed Systems
Issue number6
Publication statusPublished - Jun 2014
Externally publishedYes


  • Applications
  • pervasive computing
  • tracking
  • multiple transceiver-free objects
  • wireless sensor networks


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