DocumentCode :
582669
Title :
An improved method of self-adaptive localization for wireless sensor network in dynamic indoor environment
Author :
Ni Hu-Sheng ; Xu Wu-Jun ; Li Yuan-yuan ; Tao Meng-Yue ; Song Shi-Chao ; Fan Hong
Author_Institution :
Coll. of Inf. Sci. & Technol., Donghua Univ., Shanghai, China
fYear :
2012
fDate :
25-27 July 2012
Firstpage :
6574
Lastpage :
6577
Abstract :
According to the defects of the classic method of received-signal-strength indication (RSSI) for indoor localization, such as the larger location errors and the sensitivity to the dynamic environment, an improved self-adaptive localization method for indoor dynamic environment is proposed. In the improved method, firstly the location errors of beacon nodes are obtained by initial position based on self-amended environment path loss exponent; secondly the coordinates of the blind nodes are calculated by the location errors of beacon nodes which is used as the weights of the weighted node centralized algorithm, and the coordinate errors can be compensated; Finally, the improved method is validated on the WSN platform from NI company, and result shows that the algorithm has a higher positioning accuracy and stability in dynamic indoor environment.
Keywords :
indoor radio; sensor placement; wireless sensor networks; RSSI; WSN platform; beacon nodes; blind node coordinates; coordinate errors; dynamic indoor environment; indoor localization; location errors; received-signal-strength indication; self-adaptive localization method; weighted node centralized algorithm; wireless sensor network; Accuracy; Educational institutions; Heuristic algorithms; Indoor environments; Nickel; Wireless sensor networks; Zigbee; Indoor Localization; Received-Signal-Strength Indication; Self-Adaptive for Environment; Wireless Sensor Network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2012 31st Chinese
Conference_Location :
Hefei
ISSN :
1934-1768
Print_ISBN :
978-1-4673-2581-3
Type :
conf
Filename :
6391093
Link To Document :
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