通信学报 ›› 2017, Vol. 38 ›› Issue (12): 48-56.doi: 10.11959/j.issn.1000-436x.2017288

• 学术论文 • 上一篇    下一篇

基于压缩感知的跳频信号参数盲估计算法

付云红,张云飞,韦娟,刘乃安   

  1. 西安电子科技大学通信工程学院,陕西 西安 710071
  • 修回日期:2017-11-06 出版日期:2017-12-01 发布日期:2018-01-19
  • 作者简介:付卫红(1979-),女,湖北孝感人,博士,西安电子科技大学副教授、硕士生导师,主要研究方向为宽带无线通信、通信信号处理等。|张云飞(1992-),女,河北邢台人,西安电子科技大学硕士生,主要研究方向为跳频信号参数估计、压缩感知等。|韦娟(1973-),女,陕西渭南人,博士,西安电子科技大学副教授、硕士生导师,主要研究方向为卫星通信与移动通信等。|刘乃安(1966-),男,河南洛阳人,博士,西安电子科技大学教授、博士生导师,主要研究方向为无线通信与射频、扩展频谱通信与通信对抗等。
  • 基金资助:
    国家自然科学基金资助项目(61201134);高等学校学校引智计划基金资助项目(1308038)

Blind parameter estimation algorithm for frequency-hopping signals based on compressed sensing

Yun-hong FU,Yun-fei ZHANG,Juan WEI,Nai-an LIU   

  1. School of Electronic Engineering,Xidian University,Xi’an 710071,China
  • Revised:2017-11-06 Online:2017-12-01 Published:2018-01-19
  • Supported by:
    The National Natural Science Foundation of China(61201134);The Discipline Innovative Engineering Plan(1308038)

摘要:

针对现有的跳频信号参数估计算法没有充分考虑跳频信号频域稀疏特性的问题,提出一种基于压缩感知的跳频信号参数盲估计算法。该算法首先采用最大余弦法对经过压缩采样的跳频信号进行分段处理,估计出各段信号的跳频频率,然后,利用原子匹配的方法对含有跳变点的各段信号进行处理,精确估计出各个频率跳变时刻,进而估计跳速和起跳时刻。实验结果表明该算法在显著降低信号采样数据量和计算复杂度的同时,提高了参数估计精度。

关键词: 跳频信号, 压缩采样, 参数估计, 原子匹配

Abstract:

A blind parameter estimation algorithm for frequency-hopping signals based on compressed sensing was proposed,in order to solve the problem that the existing parameter estimation algorithms did not take into account the sparse structural characteristics of the signals in frequency domain.Firstly,the maximum cosine method was used to process the segmented compressed sampling signals,and the hopping frequency was estimated.Then,the atom matching algorithm was used to process the signal with the hopping point,and the frequency hopping instance time was estimated accurately.Then the hopping speed and hopping time were estimated.The experimental results show that the algorithm can significantly reduce the sampling data and computational complexity,while improving estimation accuracy.

Key words: frequency-hopping signal, compressive sampling, parameter estimation, atomic matching

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