基于时频矩阵局部对比度的跳频信号参数估计

刘佳敏; 赵知劲; 尚俊娜; 叶学义

doi:10.11959/j.issn.1000-0801.2021239

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基于时频矩阵局部对比度的跳频信号参数估计

研究与开发 | 更新时间：2024-06-05

- 基于时频矩阵局部对比度的跳频信号参数估计
- Parameter estimation of frequency hopping signal based on time-frequency matrix LCM
- 电信科学 2021年37卷第10期页码：126-135
- 作者机构：
  
  1. 杭州电子科技大学通信工程学院，浙江杭州 310018
  2. 中国电子科技集团第36研究所通信系统信息控制技术国家重点实验室，浙江嘉兴 314001
- 作者简介：
  
  [ "刘佳敏（1997− ），女，杭州电子科技大学硕士生，主要研究方向为软件无线电" ]
  [ "赵知劲（1959− ），女，博士，杭州电子科技大学教授、博士生导师，主要研究方向为通信信号处理、认知无线电、自适应信号处理等" ]
  [ "尚俊娜（1979− ），女，博士，杭州电子科技大学副教授，主要研究方向为通信信号处理、无线传感器网络研究、卫星导航定位" ]
  [ "叶学义（1973− ），男，杭州电子科技大学副教授，主要研究方向为图像处理、模式识别、信息隐藏" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(U19B2016)
- DOI：10.11959/j.issn.1000-0801.2021239
  中图分类号： TP414.41
- 网络出版日期：2021-10，
  
  纸质出版日期：2021-10-20
- 稿件说明：
移动端阅览
刘佳敏, 赵知劲, 尚俊娜, 等. 基于时频矩阵局部对比度的跳频信号参数估计[J]. 电信科学, 2021,37(10):126-135.

Jiamin LIU, Zhijin ZHAO, Junna SHANG, et al. Parameter estimation of frequency hopping signal based on time-frequency matrix LCM[J]. Telecommunications science, 2021, 37(10): 126-135.
刘佳敏, 赵知劲, 尚俊娜, 等. 基于时频矩阵局部对比度的跳频信号参数估计[J]. 电信科学, 2021,37(10):126-135. DOI： 10.11959/j.issn.1000-0801.2021239.

Jiamin LIU, Zhijin ZHAO, Junna SHANG, et al. Parameter estimation of frequency hopping signal based on time-frequency matrix LCM[J]. Telecommunications science, 2021, 37(10): 126-135. DOI： 10.11959/j.issn.1000-0801.2021239.

摘要

为了提高低信噪比下跳频信号参数估计性能，提出了一种基于时频矩阵局部对比度的跳频信号参数估计算法。根据跳频信号和噪声的时频分布不同特点，利用时频矩阵在不同尺度滑窗下的局部能量对比值均值，得到多尺度局部能量对比特征矩阵，通过此特征矩阵和自适应阈值分离得到仅保留了跳频信号时频信息的时频矩阵P。然后从P中提取时频跳变信息，精确估计跳频信号的跳频周期、起跳时间和跳变频率。仿真结果表明，与传统局部对比度（local contrast measure，LCM）法及形态学滤波法相比，本文算法具有更好的跳频信号提取效果和更高的参数估计精度，其有效性与实用性在DSP+FPGA的硬件系统上得到了测试验证。

Abstract

To improve the performance of the parameter estimation of frequency hopping signal under low signal-to-noise ratio

a parameter estimation algorithm of frequency hopping signal based on time-frequency matrix LCM was proposed.Considering the different characteristics of time-frequency distribution of frequency hopping signal and noise

the mean local energy comparison value of the time-frequency matrix under different scale sliding windows was used

and the multi-scale local energy comparison feature matrix was introduced

so the time-frequency matrix P that only contains the time-frequency information of the frequency hopping signal could be obtained through this feature matrix and the adaptive threshold separation.And then

by extracting the time-frequency hopping information from P

the period

hopping time and frequency of the frequency hopping signal could be accurately estimated.The simulation results show that compared with the traditional local contrast measure (LCM) and morphological filtering method

the proposed algorithm has better frequency hopping signal extraction effect and higher parameter estimation accuracy.And then the tests of the algorithm on the DSP+FPGA hardware system verify the effectiveness and practicability.

关键词

Keywords

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