DocumentCode
1921020
Title
Efficient network training method for two-dimension DOA estimation
Author
Hongguang, Chen ; Biao, Li ; Zhenkang, Shen
Author_Institution
ATR Key Lab., Nat. Univ. of Defense Technol., Changsha, China
fYear
2004
fDate
14-16 Sept. 2004
Firstpage
1028
Lastpage
1032
Abstract
Training set is vary large in two-dimensional (2D) direction estimation which prevents neural network from being widely used in 2D DOA estimation. A dimension-degraded training (DDT) method is proposed in this paper to reduce the training set. In the DDT method, elevation and azimuth are estimated in two separate neural networks respectively. We construct two 1-dimensional training sets that are much smaller than the original 2-dimensional one while keeping the high resolution of angle. Simulations show the validity of the proposed method.
Keywords
direction-of-arrival estimation; learning (artificial intelligence); neural nets; 1D training set; 2D DOA estimation; 2D direction estimation; dimension-degraded training; network training; neural network; Azimuth; Degradation; Direction of arrival estimation; Geometry; Neural networks; Phased arrays; Planar arrays; Signal resolution; Spatial resolution; Wireless communication;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Information Technology, 2004. CIT '04. The Fourth International Conference on
Print_ISBN
0-7695-2216-5
Type
conf
DOI
10.1109/CIT.2004.1357331
Filename
1357331
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