扩频信号检测、分类与参数估计研究

发布时间：2018-01-04 01:34

本文关键词：扩频信号检测、分类与参数估计研究　出处：《南京理工大学》2016年硕士论文　论文类型：学位论文

【摘要】：随着信息科学的快速发展,信息技术在各个领域得到了广泛的应用,特别是在军事通信领域,信息战已经成为现代战争的主要作战形式之一。扩频通信由于具有抗干扰和抗截获能力强、组网灵活等优点被广泛应用于军事通信领域。在军事通信对抗中,由于信噪比低并且先验知识缺乏,扩频信号的检测和识别十分困难,是当前研究的重要课题。本文主要研究了信号的盲检测,直接序列扩频信号与跳频信号的识别,跳频信号参数的估计,在总结前人理论的基础上,提出了部分改进方法。首先在频谱感知理论的基础上,介绍了低信噪比下信号的检测算法,对传统和改进的迭代算法进行了对比,提出了基于滑动平均的迭代算法,并且完成了算法的仿真。其次,介绍了时域自相关和分段傅里叶变换的算法,分别对直接序列扩频信号与跳频信号进行了识别,并提出了扩频信号的总体识别算法,对两者进行了仿真和对比。最后介绍了平滑伪魏格纳和循环自相关的算法,对跳频信号的跳周期、起跳时刻、跳频频率和码元速率等参数进行了估计,并完成了仿真。
[Abstract]:With the rapid development of information science, information technology has been widely used in various fields, especially in the field of military communications. Information warfare has become one of the main operational forms of modern warfare. Spread spectrum communication has been widely used in military communication field because of its strong anti-jamming and anti-interception ability, flexible networking and so on. Because of the low signal-to-noise ratio and lack of prior knowledge, it is very difficult to detect and recognize spread spectrum signals. The identification of direct sequence spread spectrum signal and frequency hopping signal, and the estimation of frequency hopping signal parameters. Based on the previous theories, a partial improvement method is put forward. Firstly, the spectrum sensing theory is used. This paper introduces the signal detection algorithm under low SNR, compares the traditional iterative algorithm with the improved iterative algorithm, proposes an iterative algorithm based on moving average, and completes the simulation of the algorithm. The algorithms of time domain autocorrelation and piecewise Fourier transform are introduced. The direct sequence spread spectrum signal and frequency hopping signal are identified, and the overall recognition algorithm of spread spectrum signal is proposed. Finally, the algorithms of smoothing pseudo-Wigner and cyclic autocorrelation are introduced, and the parameters of hopping period, take-off time, frequency hopping and symbol rate are estimated. The simulation is completed.
【学位授予单位】：南京理工大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TN914.42;TN911.23

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