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DOI: 10.14569/IJACSA.2014.050321
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LPA Beamformer for Tracking Nonstationary Accelerated Near-Field Sources

Author 1: Amira S. Ashour

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 5 Issue 3, 2014.

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Abstract: In this paper, a computationally very efficient algorithm for direction of arrival (DOA) as well as range parameter estimation is proposed for near-field narrowband nonstationary accelerated moving sources. The proposed algorithm based on the local polynomial approximation (LPA) beamformer, which proves its efficiency with far-field applications. The LPA estimates the instantaneous values of the direction of arrival, angular velocity, acceleration as well as the range parameters of near-field sources using weighted least squares approach which based on Taylor series. The performance efficiency of the LPA beamformer to estimate the DOAs of near-field sources is evaluated and compared with the Recursive Expectation-Maximization (REM) method. The comparison is done using standard deviation of DOA estimation error as well as for range versus signal to noise ratio (SNR). The simulation results show that LPA beamformer outperform REM1 in signal-to-noise ratio requirements.

Keywords: Near-field; range and DOA estimation, moving source tracking; LPA beamformer; REM (Recursive Expectation Maximization)

Amira S. Ashour, “LPA Beamformer for Tracking Nonstationary Accelerated Near-Field Sources” International Journal of Advanced Computer Science and Applications(IJACSA), 5(3), 2014. http://dx.doi.org/10.14569/IJACSA.2014.050321

@article{Ashour2014,
title = {LPA Beamformer for Tracking Nonstationary Accelerated Near-Field Sources},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2014.050321},
url = {http://dx.doi.org/10.14569/IJACSA.2014.050321},
year = {2014},
publisher = {The Science and Information Organization},
volume = {5},
number = {3},
author = {Amira S. Ashour}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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