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Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS)

ISSN:2141-7016

Article Title: Performance Evaluation of Correlative Interferometry for Angle of Arrival Estimation
by Suhail M. Kamal, Ashraf A. Adam, Abimbola S. Ajagun

Abstract:
The paper proposes the implementation of correlative interferometry for angle of arrival (AOA) estimation. The correlative interferometry processing involves the comparison of the measured phase differences between the antenna elements of the direction finder (DF) antenna system with those obtained for the same antenna system at all possible directions of incidence. The comparison is made by calculating the correlation of the two data sets obtained by multiplying the coordinates element by element and summing the result. Using different comparison data sets for different wave directions, the bearing is estimated from the data set for which the correlation is at a maximum. Four and eight uniform linear array (ULA) configuration of the algorithm is investigated so that that the amount of processing and memory was optimized with accuracy in the measurement of the direction. From the optimum structure, Monte Carlo simulation is carried out to evaluate the mean and variance of multiple AOA estimates for various signal-to-noise ratios (SNR). Results obtained shows that eight element ULA performs better than the four element ULA due to its higher resolution, with earlier having an average AOA estimate of 10dB and the latter of 12dB. This paper caters for the high processing burden associated with direction finding, provides a significant relationship between the number of ULA elements, resolution and effect of noise in AOA estimation for direction finding. This paper presents a critical evaluation on the superiority of correlative interferometry for AOA estimation.
Keywords: correlative interferometry, angle of arrival (AOA), direction finder (DF), uniform Linear Array (ULA), Monte Carlo
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ISSN: 2141-7016

Editor in Chief.

Prof. Gui Yun Tian
Professor of Sensor Technologies
School of Electrical, Electronic and Computer Engineering
University of Newcastle
United Kingdom

 

 

Copyright © Journal of Emerging Trends in Engineering and Applied Sciences 2010