Fine-Grained Localization for Multiple Transceiver-Free Objects by using RF-Based Technologies

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 t...

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Bibliographic Details
Published in:IEEE transactions on parallel and distributed systems Vol. 25; no. 6; pp. 1464 - 1475
Main Authors: Dian Zhang, Kezhong Lu, Rui Mao, Yuhong Feng, Yunhuai Liu, Zhong Ming, Ni, Lionel M.
Format: Journal Article
Language:English
Published: New York IEEE 01.06.2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Accuracy
Algorithms
Applications
Calibration
Clustering algorithms
Dynamics
Heuristic algorithms
Localization
multiple transceiver-free objects
pervasive computing
Position (location)
Receivers
Sensors
Tracking
Wireless communication
Wireless sensor networks
ISSN:1045-9219, 1558-2183
Online Access:Get full text
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Summary: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.
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ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2013.243