Underdetermined DOA estimation of coherent signals based on denoising complex FastICA and sparse reconstruction
To solve the problem that most of the existing direction of arrival(DOA) estimation methods for coherent signals could not be used in the case of under determination, where the number of incident signals exceeds the number of sensors, a DOA estimation method combining complex fast independent compon...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2021-11-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021219/ |
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| Summary: | To solve the problem that most of the existing direction of arrival(DOA) estimation methods for coherent signals could not be used in the case of under determination, where the number of incident signals exceeds the number of sensors, a DOA estimation method combining complex fast independent component analysis (FastICA) and sparse reconstruction algorithm was proposed.When the number of uniform circular array(UCA) sensors was M, the DOA of M(M-1) incident signals could be estimatedat most.To solve the problem of poor separation effect of complex FastICA in the case of low signal-to-noise ratio(SNR), two general denoising complex FastICA algorithm were proposed, which could be used in the case of circular signal and non-circular signal.The results of simulation and measured data show that the proposed algorithm can estimate both coherent and incoherent signals in underdetermined cases.Compared with several existing algorithm, the proposed DOA estimation algorithm has good performance. |
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| ISSN: | 1000-436X |