Affiliation:
1. Institute of IoT Engineering, Shanghai Business School, Shanghai 201400, China
2. Electronic Information College, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Abstract
This paper presents a new enhanced coprime array for direction of arrival (DOA) estimation. Coprime arrays are capable of estimating the DOA using coprime properties and outperforming uniform linear arrays. However, the associated algorithms are not directly applicable for estimating the DOA of coherent sources. To overcome this limitation, we propose an enhanced coprime array in this paper. By increasing the number of array sensors in the coprime array, it is feasible to enlarge the aperture of the array and these additional array sensors can be utilized to achieve spatial smoothing, thus enabling estimation of the DOA for coherent sources. Additionally, applying the spatial smoothing technique to the signal subspace, instead of the conventional spatial smoothing method, can further improve the ability to reduce noise interference and enhance the overall estimation result. Finally, DOA estimation is accomplished using the MUSIC algorithm. The simulation results demonstrate improved performance compared to traditional algorithms, confirming its feasibility.
Reference34 articles.
1. Robust adaptive beamforming based on interference covariance matrix sparse reconstruction;Gu;Signal Process.,2014
2. Johnson, D.H., and Dudgeon, D.E. (1993). Array Signal Processing: Concepts and Techniques, Prentice Hall.
3. General direction-of-arrival estimation: A signal subspace approach;Cadzow;IEEE Trans. Aerosp. Electron. Syst.,1989
4. Two decades of array signal processing research: The parametric approach;Krim;IEEE Signal Process. Mag.,1996
5. Famoriji, O.J., and Shongwe, T. (2023). Deep Learning Approach to Source Localization of Electromagnetic Waves in the Presence of Various Sources and Noise. Symmetry, 15.
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