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A new indoor location technology using back propagation neural network to fit the RSSI-d curve

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2 Author(s)
Huiqing Zhang ; Coll. of Electron. Inf. & Control Eng., Beijing Univ. of Technol., Beijing, China ; Xiaowei Shi

After lots of research and analysis of the RSSI-d(received signal strength indicator RSSI and distanced) relationship between the reference nodes and blind nodes, A new indoor WLAN location technology using BP neural network to fit the RSSI-d curve is proposed. Firstly, establish a three-layer BP neural network, the input layer of the network is RSSI, through the hidden layer processing, the final output from the output layer is distance d between the reference node and blind node. Once get three more such distance d, according to the known coordinates of the reference nodes, Taylor series expansion algorithm is used to determine the coordinates of the blind node. Finally, the experiment result shows that the new algorithm improves the positioning accuracy and universality, compared with the traditional positioning algorithms.

Published in:

Intelligent Control and Automation (WCICA), 2012 10th World Congress on

Date of Conference:

6-8 July 2012

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