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Single channel source separation and parameter estimation of multi-component PRBCPM-SFM signal based on generalized period

机译:基于广义周期的多分量PRBCPM-SFM信号的单通道源分离与参数估计

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This paper proposes an approach of single channel source separation and parameter estimation of multi-component PRBCPM-SFM (pseudo-random binary code phase modulated sinusoidal frequency modulation) signal. By transforming all components to SFM signals through square calculation, we may then apply singular value decomposition to determine the generalized period and the modulation frequency of the SFM signal. The modulation index and carrier frequency are determined by searching for discrete points and optimizing calculations. The initial phase can be determined by calculating the inner product. Finally, given that the pseudo-random binary code is a real signal, the PN (Pseudo-noise) sequence and the amplitude can be estimated. Our proposed method can estimate the SNR by using the method of subspace-based decomposition, and the estimated SNR can be used to adaptively stop separation. Experimental results demonstrate the algorithm's performance. (C) 2015 Elsevier Inc. All rights reserved.
机译:本文提出了一种多分量PRBCPM-SFM(伪随机二进制码相位调制正弦频率调制)信号的单通道源分离和参数估计的方法。通过平方计算将所有分量转换为SFM信号,然后可以应用奇异值分解来确定SFM信号的广义周期和调制频率。通过搜索离散点并优化计算来确定调制指数和载波频率。初始阶段可以通过计算内积来确定。最后,假设伪随机二进制代码是真实信号,则可以估计PN(伪噪声)序列和幅度。我们提出的方法可以使用基于子空间的分解方法来估计信噪比,并且所估计的信噪比可以用于自适应地停止分离。实验结果证明了该算法的性能。 (C)2015 Elsevier Inc.保留所有权利。

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