Time-Frequency Spatial Smoothing MUSIC Algorithm for DOA Estimation Based on Co-prime Array
In this paper, the time-frequency spatial smoothing MUSIC algorithm (TF-SSMUSIC) for DOA estimation based on co-prime array is proposed. The spatial smoothing MUSIC (SSMUSIC) is a typical DOA estimation algorithm based on co-prime array. TF-SSMUSIC replaces SSMUSIC’s data covariance matrix with a time-frequency distribution matrix, which leads to a better DOA estimation performance. By selecting points in the time-frequency domain, not only the signal-to-noise ratio (SNR) can be improved effectively, but the signal interference in different time-frequency domains can be isolated. The improvement of SNR makes TF-SSMUSIC have a more accurate DOA estimation than SSMUSIC in the case of low SNR. Especially, if source signals are separable in the time-frequency domain, TF-SSMUSIC can process them solely. In this way, the angle resolution and the number of predictable source signals can be improved greatly.
KeywordsDOA estimation Time-frequency Co-prime array Spatial smoothing MUSIC
This work was supported in part by the National Key R&D Program of China under Grant 2017YFC1405202, in part by the National Natural Science Foundation of China under Grant 61571159 and Grant 61571157, and in part by the Public Science and Technology Research Funds Projects of Ocean under Grant 201505002.
- 2.Chen S, Li X, Shao Z. Study on the performance of DOA estimation algorithms. In: IEEE international conference on communication problem-solving. IEEE; 2016. p. 475–7.Google Scholar
- 3.Li F. Time-frequency DOA estimation and application comprehensive polarization information. Harbin: Harbin Institute of Technology; 2016.Google Scholar
- 5.Pal P, Vaidyanathan PP. Co-prime sampling and the music algorithm. In: Digital signal processing workshop and IEEE signal processing education workshop. IEEE; 2011. p. 289–94.Google Scholar
- 7.Xiong J, Chen S. Direction of arrived estimation based on the co-prime arrays. In: Fourth international conference on information science and industrial applications. IEEE; 2016. p. 21–4.Google Scholar