DocumentCode
653226
Title
An Improved Location Algorithm Based on CC2431
Author
Yinghui Kong ; Qingqing Yang
Author_Institution
Electron. & Commun. Eng., North China Electr. Power Univ., Baoding, China
fYear
2013
fDate
20-23 Aug. 2013
Firstpage
646
Lastpage
652
Abstract
In ranging technology-based positioning algorithm, after getting the distance between nodes using RSSI ranging, we can use trilateration method, triangulation method or maximum likelihood estimation algorithms to calculate the position of the blind node. In the real environment, the radio transmission path loss, antenna height, antenna angle of the obstacle, the electromagnetic wave interference and other factors have a significant impact to its received signal strength measurement and we can optimize the main parameter and exclude the maximum error by measuring and analyzing. And we have proposed the improved weighted centroid localization algorithm based on the CC2431 and the implementation of the algorithm change over the hardware. the improved algorithm proposed in this paper improved the positioning accuracy effectively, and achieved a well positioning results.
Keywords
electromagnetic interference; maximum likelihood estimation; mobile computing; wireless sensor networks; CC2431; RSSI ranging; antenna angle; antenna height; blind node; electromagnetic wave interference; maximum likelihood estimation algorithms; positioning accuracy; radio transmission path loss; ranging technology-based positioning algorithm; received signal strength measurement; triangulation method; trilateration method; weighted centroid localization algorithm; Accuracy; Engines; Maximum likelihood detection; Nonlinear filters; Propagation losses; Wireless communication; Wireless sensor networks; CC2431 location engines; Improved localization algorithm; RSSI; transmission model;
fLanguage
English
Publisher
ieee
Conference_Titel
Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing
Conference_Location
Beijing
Type
conf
DOI
10.1109/GreenCom-iThings-CPSCom.2013.119
Filename
6682133
Link To Document