| 小波频率估计方法及其在通信信号检测中的应用 |
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| 引用本文： | 张煜东,李铜川,王水花,吴乐南.小波频率估计方法及其在通信信号检测中的应用[J].南京气象学院学报,2011(4):319-323. |
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| 作者姓名： | 张煜东 李铜川 王水花 吴乐南 |
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| 作者单位： | 东南大学信息科学与工程学院, 南京, 210096;华航无线电测量研究所, 北京, 100013;东南大学信息科学与工程学院, 南京, 210096;东南大学信息科学与工程学院, 南京, 210096 |
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| 基金项目： | 国家自然科学基金(60872075);国家高技术发展计划(2008AA01Z227) |
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| 摘 要： | 小波变换作为新的信号分析工具,受到学者们的重视,然而如何将小波尺度与频率联系起来,是一个亟待解决的问题.为了求解小波的中心频率,提出了一种基于正弦波的模型,并将模型推广到任意采样间隔与任意小波尺度.由于模型的非凸性,传统的基于梯度的优化方法容易陷入局部最优,因此提出了一种基于Rossler吸引子的粒子群算法.实验给出了常见小波的频率值,并通过一个通信信号检测的例子证明了该方法的有效性.
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| 关 键 词： | 小波变换 连续小波变换 尺度与频率 粒子群算法 Rossler吸引子 |
| 收稿时间： | 2010/10/26 0:00:00 |
Wavelet frequency estimation method and its application in communication signal detection |
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| ZHANG Yudong,LI Tongchuan,WANG Shuihua and WU Lenan.Wavelet frequency estimation method and its application in communication signal detection[J].Journal of Nanjing Institute of Meteorology,2011(4):319-323. |
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| Authors: | ZHANG Yudong LI Tongchuan WANG Shuihua and WU Lenan |
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| Institution: | School of Information Science & Engineering, Southeast University, Nanjing 210096;Huahang Institute of Radio Measurement, Beijing 100013;School of Information Science & Engineering, Southeast University, Nanjing 210096;School of Information Science & Engineering, Southeast University, Nanjing 210096 |
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| Abstract: | As a latest signal analysis toolkit,wavelet transform receives increasing interest from scholars.However, the correlation between the wavelet scale and frequency is an outstanding problem.This paper proposed a sinusoid model to estimate the central frequency of mother wavelets,besides,the model is generalized to the situation of arbitrary sample interval and arbitrary scale of wavelet.Moreover,traditional gradient-based optimization method will find local optimum due to the non-convex property of the model,therefore,a novel Rossler-attractor based Particle Swarm Optimization(RPSO)method was proposed.Experiments gave the center frequencies of all common wave-lets,and applied the proposed method in the field communication signal detection to validate its effectiveness and efficiency. |
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| Keywords: | wavelet transform continuous wavelet transform scale and frequency particle swarm optimization Rossler attractor |
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