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Fine-Grained Localization for Multiple Transceiver-Free Objects by using RF-Based Technologies
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DOI：10.1109/TPDS.2013.243.png)
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Abstract
En 中文
In traditional radio-based localization methods, the target object has to carry a transmitter (e. g., active RFID), a receiver (e.g., 802.11 x 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.
Keywords:
Applications
pervasive computing
tracking
wireless sensor networks
multiple transceiver-free objects
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