DocumentCode
2767720
Title
Multisensor Data Fusion Using Neural Networks
Author
Yadaiah, N. ; Singh, Lakshman ; Bapi, R.S. ; Rao, V. Srinivasa ; Deekshatulu, B.L. ; Negi, Atul
Author_Institution
Jawaharlal Nehru Technol. Univ., Hyderabad
fYear
0
fDate
0-0 0
Firstpage
875
Lastpage
881
Abstract
This paper presents a Hebbian learning based linear single-layer neural network based measurement fusion of multisensor data. The performance of the proposed unsupervised neural network algorithm is compared with traditional fusion methods based on Kalman filtering such as measurement fusion and state vector fusion. The experiments have been carried out using multisensor data obtained from different radars. The results demonstrate the viability of the proposed algorithm.
Keywords
Kalman filters; neural nets; sensor fusion; Kalman filtering; hebbian learning; linear single-layer neural network; measurement fusion; multisensor data fusion; radars; state vector fusion; unsupervised neural network algorithm; Assembly systems; Computer networks; Data engineering; Electric variables measurement; Hebbian theory; Intelligent sensors; Kalman filters; Neural networks; Radar detection; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location
Vancouver, BC
Print_ISBN
0-7803-9490-9
Type
conf
DOI
10.1109/IJCNN.2006.246777
Filename
1716188
Link To Document