利用粒子群算法实现PPS信号的稀疏分解

针对在分析高阶多项式相位信号（PPS）时，Wigner—Ville分布（WVD）的交叉项使得时频分布图变得难以解释，为了提高信号计算速度和数据提取精度，采用基于匹配追踪（MP）算法的信号稀疏分解来抑制交叉项，但是稀疏分解计算量大，难以应用在实时信号处理。将粒子群优化算法用于稀疏分解的最优匹配原子的搜索，能降低稀疏分解复杂度，同时减少稀疏分解的超完备字典对存储空间的占用，可以提高用稀疏分解理论进行信号处理的计算效率，满足或接近实时性的要求。计算机仿真结果证实了方法的有效性。

Sparse Decomposition of Polynomial Phase Signals with Particle Swarm Optimization

For the analysis of high order polynomial phase signals,the figure of time-frequency distribution becomes difficult to understand due to cross-terms in the Wigner-Ville distribution(WVD).Cross-term suppression is obtained by using spare decomposition based on matching pursuit(MP),but the computational burden in signal sparse decomposition process is so huge that it is almost impossible to apply it to real time signal processing.To reduce complexity of sparse decomposition and space of memory,particle swarm ...