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A complex mixing matrix estimation algorithm in under-determined blind source separation problems

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Abstract

This paper considers the complex mixing matrix estimation in under-determined blind source separation problems. The proposed estimation algorithm is based on single source points contributed by only one source. First, the problem of complex matrix estimation is transformed to that of real matrix estimation to lay the foundation for detecting single source points. Secondly, a detection algorithm is adopted to detect single source points. Then, a potential function clustering method is proposed to process single source points in order to get better performance. Finally, we can get the complex mixing matrix after derivation and calculation. The algorithm can estimate the complex mixing matrix when the number of sources is more than that of sensors, which proves it can solve the problem of under-determined blind source separation. The experimental results validate the efficiency of the proposed algorithm.

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Acknowledgments

This work is supported by National Natural Science Foundation of China (No. 51509049), the Heilongjiang Province Natural Science Foundation (Nos. F201345 and QC2016081) and the Fundamental Research Funds for the Central Universities of China (No. GK2080260140).

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Authors and Affiliations

  1. College of Information and Communication Engineering, Harbin Engineering University, Harbin, 150001, China

    Yibing Li, Wei Nie, Fang Ye & Qiuying Wang

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  1. Yibing Li
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  2. Wei Nie
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  3. Fang Ye
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  4. Qiuying Wang
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Correspondence to Fang Ye.

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Li, Y., Nie, W., Ye, F. et al. A complex mixing matrix estimation algorithm in under-determined blind source separation problems. SIViP 11, 301–308 (2017). https://doi.org/10.1007/s11760-016-0937-y

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  • DOI: https://doi.org/10.1007/s11760-016-0937-y

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