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一种TDCS信号检测及基函数周期估计的方法

侯文达, 付天晖

侯文达, 付天晖. 一种TDCS信号检测及基函数周期估计的方法[J]. 信号处理, 2023, 39(5): 866-874. DOI: 10.16798/j.issn.1003-0530.2023.05.011
引用本文: 侯文达, 付天晖. 一种TDCS信号检测及基函数周期估计的方法[J]. 信号处理, 2023, 39(5): 866-874. DOI: 10.16798/j.issn.1003-0530.2023.05.011
HOU Wenda, FU Tianhui. A Method of TDCS Signal Detection and Basis Function Period Estimation[J]. JOURNAL OF SIGNAL PROCESSING, 2023, 39(5): 866-874. DOI: 10.16798/j.issn.1003-0530.2023.05.011
Citation: HOU Wenda, FU Tianhui. A Method of TDCS Signal Detection and Basis Function Period Estimation[J]. JOURNAL OF SIGNAL PROCESSING, 2023, 39(5): 866-874. DOI: 10.16798/j.issn.1003-0530.2023.05.011

一种TDCS信号检测及基函数周期估计的方法

基金项目: 

国家自然科学基金 42174051

详细信息
    作者简介:

    侯文达 男,1997年生,山东潍坊人。海军工程大学硕士研究生,主要研究方向为变换域通信、通信信号处理等。E-mail:hgdy808@163.com

    付天晖 男,1981年生,黑龙江大庆人。海军工程大学博士,海军工程大学副教授,硕士生导师。主要研究方向为抗干扰通信、透地通信、通信信号处理等。E-mail:fthyes@yeah.net

A Method of TDCS Signal Detection and Basis Function Period Estimation

  • 摘要: 针对变换域通信系统(Transform Domain Communication System, TDCS)信号难以检测的问题,设计了基于功率谱二次处理的检测方法。通过数学建模,理论推导了TDCS信号的自相关函数,并由此推出了TDCS信号的两次功率谱函数,证明了TDCS信号的二次功率谱存在周期性谱峰的特征,并给出了谱峰周期与基函数周期的数学关系。据此设计了一种TDCS信号检测算法,该算法能够检测TDCS信号并对基函数周期给予估计。理论分析了高斯白噪声对检测算法的影响,通过计算机仿真,验证了该算法在低信噪比下的性能,对比了二次功率谱法与时域相关法的检测性能,验证了采样数据长度对检测性能的影响。仿真结果表明在低信噪比条件下,本文算法对基函数周期估计仍有效,且算法性能相较于自相关法提高了约1.5 dB,增加采样数据长度可进一步提高二次功率谱算法的准确性。
    Abstract: ‍ ‍Aiming at the problem that TDCS signal is difficult to detect, a detection method based on secondary processing of power spectrum is designed. The secondary power spectrum function of TDCS signal was theoretically deduced by mathematical modeling. Moreover, the secondary power spectrum of TDCS signal was proved that has the characteristics of periodic peaks, and the relationship between the spectral peak period and the basis function period was given. Accordingly, a TDCS signal detection algorithm is designed, which can detect the TDCS signal and estimate the period of the basis function. Through computer simulation, the performance of the algorithm under low signal-to-noise ratio was verified, and the detection performance of the secondary power spectrum method and the time-domain correlation method were compared. The simulation results show that under the condition of low signal-to-noise ratio, the algorithm proposed in this paper is still effective in estimating the period of the basis function, and the performance of the algorithm is improved by about 1.5 dB compared with the autocorrelation method. In addition, increasing the number of sampling points can further improve the accuracy of the secondary power spectrum algorithm.
  • 图  1   TDCS频谱感知结果示意图

    Figure  1.   Schematic diagram of TDCS spectrum sensing results

    图  2   TDCS原理框图

    Figure  2.   Block Diagram of a TDCS

    图  3   二次功率谱检测器

    Figure  3.   Secondary power spectrum detector

    图  4   自相关函数计算示意图

    Figure  4.   Schematic diagram of autocorrelation function calculation

    图  5   TDCS信号检测算法流程

    Figure  5.   TDCS signal detection algorithm flow

    图  6   TDCS信号二次功率谱

    Figure  6.   Secondary power spectrum of TDCS signal

    图  7   信噪比-19 dB、-17 dB时TDCS信号的二次功率谱

    Figure  7.   Secondary power spectrum of TDCS signal when SNR is -19 dB and -17 dB

    图  8   不同信噪比下检测性能曲线

    Figure  8.   Detection performance curves under different SNR

    图  9   TDCS信号自相关图

    Figure  9.   Autocorrelation diagram of TDCS signal

    图  10   不同算法检测性能比较

    Figure  10.   Detection performance of different algorithms

    图  11   不同采样长度下检测性能曲线

    Figure  11.   Detection performance curves under different sampling lengths

    表  1   Ra,bτ0)函数值

    Table  1   Ra,bτ0) function value

    码元分布相关值τ0=0τ0=N/2
    ma =0 mb =0Ra,b (τ0)=Rs0s0(τ0)εs0
    ma =0 mb =1Ra,b (τ0)=Rs0s1(τ0)0εs /2
    ma =1 mb =0Ra,b (τ0)=Rs1s0(τ0)0εs /2
    ma =1 mb =1Ra,b (τ0)=Rs1s1(τ0)εs0
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  • 收稿日期:  2022-08-07
  • 刊出日期:  2023-05-24

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