NDLI: Application of neural networks in spatial signal processing (invited paper)

Content Provider	IEEE Xplore Digital Library
Author	Milovanovic, B. Agatonovic, M. Stankovic, Z. Doncov, N. Sarevska, M.
Copyright Year	2012
Description	Author affiliation: Faculty of Psychology, Ruhr-University Bochum, Universitaetsstr. 150, 44801, Germany (Sarevska, M.) \|\| Faculty of Electronic Engineering, University of Niš, Aleksandra Medvedeva 14, 18000, Serbia (Milovanovic, B.; Agatonovic, M.; Stankovic, Z.; Doncov, N.)
Abstract	Neural networks (NNs) have proven to be a very powerful tool both for one-dimensional (1D) and two-dimensional (2D) direction of arrival (DOA) estimation. By avoiding complex and time-consuming mathematical calculations, NNs estimate DOAs almost instantaneously. This feature makes them very convenient for real-time applications. Further, unlike the well known MUSIC algorithm, neural network-based models provide accurate directions without additional calibration procedure of antenna array and a priori knowledge of the number of sources. In this review paper, the results achieved by the research group at the Faculty of Electronic Engineering in Nis are presented. The problem of DOA estimation of narrowband signals impinging upon different configurations of antenna arrays is addressed. Both Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) neural networks are considered, and their advantages and disadvantages are discussed. To improve the resolution of DOA estimates, sectorization model is introduced. As shown in this work, neural network-based models demonstrate high-resolution localization capabilities and much better efficiency than the MUSIC.
Starting Page	5
Ending Page	14
File Size	613923
Page Count	10
File Format	PDF
ISBN	9781467315692
e-ISBN	9781467315722
DOI	10.1109/NEUREL.2012.6419950
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-20
Publisher Place	Serbia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Direction of arrival estimation Arrays Estimation Vectors Artificial neural networks Multiple signal classification Neurons MUSIC Neural networks SDMA DOA spatial signal processing
Content Type	Text
Resource Type	Article

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