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Enhanced DOA Estimation Using Eigenvalue Reconstruction and Toeplitz Preprocessing

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Abstract

Reliable direction of arrival (DOA) estimation is crucial for the performance of wireless communication systems. In this paper, we introduce a refined DOA estimation method that combines eigenvalue reconstruction of the noise subspace and Toeplitz preprocessing with the multiple signal classification (MUSIC) algorithm. The proposed technique enhances the consistency of the noise subspace and improves the algorithm’s resolution. Extensive simulations demonstrate that the method outperforms both the standard MUSIC and the MUSIC with Eigenvalue Reconstruction (MUSIC_ER) techniques. Notably, our approach shows enhanced performance in terms of the root mean square error (RMSE) across snapshot ranges from 1 to 10. These enhancements make the proposed method (MUSIC_TR) a practical and effective option, especially in low-snapshot scenarios, providing an alternative solution for DOA estimation.

Keywords

DOA MUSIC Toeplitz preprocessing radar wireless communication

Authors

S. Ali
Department of Electrical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand
S. Khichar
Department of Electrical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand
A. Bajpai
Department of EECE, GITAM University MURTI Research Centre, Bangalore
L. Wuttisittikulkij
Department of Electrical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand
P. Vanichchanunt
Department of Electrical Engineering and Computer Engineering Faculty of Engineering, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand

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proceedings
Publisher
IEEE
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