时频面滑窗掩膜的多分量信号高效重构算法

An Efficient Multi-component Signals Reconstruction Algorithm Using Masking Technique Based on Sliding Window in Time-frequency Plane

针对基于特征值分解的Wigner-Ville分布信号重构算法运算复杂度高这一问题,该文提出一种高效多分量信号重构算法。首先,通过分析Wigner-Ville逆变换公式,推导出瞬时时刻重构序列与原序列之间的联系,提出一种高效的信号重构算法。然后,采用平滑伪Wigner-Ville分布作为时频掩膜抑制Wigner-Ville分布的交叉项,并通过在时频面内滑窗的方法逐一提取各分量信号。最后,结合高效信号重构算法和时频面滑窗掩膜技术,实现多分量信号快速准确重构。仿真实验证明了该算法的有效性和可行性。

Due to the huge computation for eigenvalue decomposition based signal synthesis method, an efficient multi-component signals reconstruction algorithm is presented in this paper. Firstly, by analyzing the inverse transformation for Wigner-Ville distribution, a fast signal reconstruction is developed using the inherent relationship between original signal and synthesized signal. Then, the smoothed pseudo Wigner-Ville distribution is used as a time-frequency masking to suppress the cross-terms, and the sliding window method in time-frequency plane is adopted to extract signals one by one. Finally, by combining the signal synthesis algorithm and the sliding window masking method, multi-component signals reconstruction can be realized efficiently and accurately. Simulation results demonstrate the effectiveness and feasibility of the proposed algorithm.