Title :
Localization algorithm based on NMDS-MLE-RSSI
Author :
Jianxin, Ao ; Yuzhen, Liu
Author_Institution :
Liaoning Tech. Univ., Huludao, China
Abstract :
Considering random error of RSSI value in the NMDS-RSSI localization algorithm, the maximum likelihood estimation (Maximum Likelihood Estimation, MLE) is introduced, using several average measurements after several measurements effectively reduces the error of RSSI values, this paper gives the NMDS-MLE-RSSI localization algorithm and network communication model of the algorithm, then simulates NMDS-MLE-RSSI algorithm with MATLAB, simulation tests verify the positioning is better. Because the RSSI value is easy to jump in practical and at mine tunnel application environment, it weights the coordinates of the anchor nodes with RSSI that is between anchor and position-unknown node, Then calculates the coordinate of unknown node by average weighted coordinates of several anchors.
Keywords :
indicators; maximum likelihood estimation; NMDS RSSI localization algorithm; maximum likelihood estimation; network communication model; random error; wireless signal strength indicator; Accuracy; Algorithm design and analysis; Computers; Maximum likelihood estimation; Measurement uncertainty; Position measurement; Wireless sensor networks;
Conference_Titel :
Computational Problem-Solving (ICCP), 2010 International Conference on
Conference_Location :
Lijiang
Print_ISBN :
978-1-4244-8654-0