基于广义周期性的单通道多分量正弦调频信号分离和参数估计

发布时间：2018-02-15 12:40

本文关键词： 信号处理多分量正弦调频信号信号分离参数估计广义周期性自适应阈值　出处：《电子与信息学报》2014年10期 　论文类型：期刊论文

【摘要】：针对噪声条件下的单通道多分量正弦调频(SFM)信号,该文提出一种信号分离和参数提取方法。利用正弦调频信号的广义周期性进行奇异值分解,以求出分量信号的调制频率;通过离散点搜索,估计出分量信号的调频(FM)初始相位、调制指数及载频,并对这些估计值利用信赖域算法进行优化,减小误差;利用内积计算,估计分量信号的幅度和初始相位。此外,还利用自相关矩阵特征值分解估计混合信号的信噪比(SNR),并根据信噪比确定停止分解的阈值。在仿真与分析中,针对具体的信号详细说明了该方法的各步骤,并在不同信噪比条件下分析了该方法的参数估计精确度。
[Abstract]:In this paper, a method of signal separation and parameter extraction is proposed for single channel multi-component sinusoidal frequency modulation (SFM) signals under noise conditions. The singular value decomposition of sinusoidal frequency modulated signals is carried out by using generalized periodicity of sinusoidal frequency modulated signals to obtain the modulation frequency of component signals. The initial phase, modulation exponent and carrier frequency of FM of component signal are estimated by discrete point search, and these estimations are optimized by using trust region algorithm to reduce the error, and the inner product is used to calculate the initial phase, the modulation exponent and the carrier frequency. The amplitude and initial phase of component signal are estimated. In addition, the SNR of mixed signal is estimated by eigenvalue decomposition of autocorrelation matrix, and the threshold of stopping decomposition is determined according to SNR. In simulation and analysis, The steps of the method are described in detail for specific signals, and the accuracy of parameter estimation is analyzed under different signal-to-noise ratio (SNR) conditions.
【作者单位】：南京理工大学电子工程与光电技术学院;解放军73015部队;
【基金】：国家自然科学基金(61301216) 省部级基金资助课题
【分类号】：TN911.23

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