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http://dx.doi.org/10.5394/KINPR.2003.27.4.465

Real Time AOA Estimation Using Analog Neural Network Model  

Jeong, Jung-Sik (Division of Maritime Transportation System, Mokpo National University)
Publication Information
Journal of Navigation and Port Research / v.27, no.4, 2003 , pp. 465-469 More about this Journal
Abstract
It has well known that MUSIC and ESPRIT algorithms estimate angle of arrival(AOA) with high resolution by eigenvalue decomposition of the covariance matrix which were obtained from the array antennas, However, the disadvantage of MUSIC and ESPRIT is that they are computationally ineffective, and then they are difficult to implement in real time. the other problem of MUSIC and ESPRIT is to require calibrated antennas with uniform features, and are sensitive ti the manufacturing fault and other physical uncertainties. To overcome these disadvantages, several method using neural model have been study. For multiple signals, those methods require huge training data prior to AOA estimation. This paper proposes the algorithm for AOA estimation by interconnected Hopfield neural model. Computer simulations show the validity of the proposed algorithm. It follows that the proposed method yields better AOA estimates than MUSIC. Moreover, out method does not require huge training procedure and only assigns interconnected coefficients to the neural network prior to AOA estimation.
Keywords
array antenna; radar signal processing; AOA; neural network; Hopfield model; MUSIC;
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Times Cited By KSCI : 1  (Citation Analysis)
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