Systems Engineering and Electronics
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AI Xiao-fan, LUO Yong-jiang, ZHAO Guo-qing
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Abstract:
Considering the underdetermined blind separation of radar signals which is non-disjoint in timefrequency domain, a method based on observed signals and the cumulant is proposed for estimating matrix, and then the modified subspace projection is used for recovering radar signal. Firstly, the fourth-order cumulant is constructed based on observed signals and the cumulant is expressed as the third-order tensor, the mixed matrix is estimated by tensor decomposition with enhanced line search alternating least square. Finally, the over-determined matrix, which is calculated by estimating the column vector corresponds to the active original signal at any time-frequency point, is used to complete the estimation of signal by Moore-Penrose. The proposed method can solve the blind separation of non-disjoint radar signals in the time-frequency domain under complex electromagnetic environment. Simulation results show that the proposed method outperforms the existing methods in mixed matrix estimation and source recovery.
AI Xiao-fan, LUO Yong-jiang, ZHAO Guo-qing. Underdetermined blind separation of radar signals based on tensor decomposition[J]. Systems Engineering and Electronics, doi: 10.3969/j.issn.1001-506X.2016.11.09.
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URL: https://www.sys-ele.com/EN/10.3969/j.issn.1001-506X.2016.11.09
https://www.sys-ele.com/EN/Y2016/V38/I11/2505