一种基于时频分析的多跳频信号盲源分离算法
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国家自然科学基金面上项目(62071481)


A Blind Source Separation Algorithm for Multi-frequency Hopping Signals Based on Time-frequency Analysis
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    摘要:

    针对多个无人机遥控信号的分离问题,提出一种基于时频分析进行数据处理的多跳频(frequency hopping, FH)信号盲源分离(blind source separation,BSS)算法。利用不同跳周期的跳频信号驻留时间的差异性,改进时频脊 线的提取;利用小波变换检测改进后时频脊线的突变点,求脊线最大驻留时间即为跳频信号中的最小跳周期;分离 出不同跳周期的跳频信号,并基于时频能量值的不同,对不同信号幅度的跳频信号进行盲源分离。结果表明:与同 类算法相比,该算法在不依赖多通道数据的采集及混合矩阵估计等情况下,可实现单通道情况下多跳频信号的盲源 分离,具有一定的工程应用价值。

    Abstract:

    Aiming at the separation problem of multiple UAV remote control signals, a blind source separation algorithm of multiple frequency hopping signals based on time-frequency analysis is proposed. The difference of the dwell time of FH signals with different hopping periods is used to improve the extraction of the time-frequency ridge.The wavelet transform is used to detect the mutation point of the improved time-frequency ridge, and the maximum dwell time of the ridge is the minimum hopping period of FH signals. The frequency hopping signals with different hopping periods are separated, and the frequency hopping signals with different signal amplitudes are subjected to blind source separation based on different time-frequency energy values. The results show that compared with the similar algorithms, the proposed algorithm can realize the blind source separation of multi-frequency hopping signals in the case of single channel without relying on multi-channel data acquisition and mixing matrix estimation, and has certain engineering application value.

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侯 范.一种基于时频分析的多跳频信号盲源分离算法[J].,2022,41(5).

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  • 收稿日期:2022-01-27
  • 最后修改日期:2022-02-26
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  • 在线发布日期: 2022-05-05
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