直扩信号侦察的关键技术研究

发布时间：2018-10-24 21:50

【摘要】：由于扩频通信具有展宽频带、检测概率低、抗干扰能力强等优良特点,使得扩频通信在军事和民用上都得到了广泛的应用。而其中直接序列扩频通信是扩频通信系统中比较常用的一种扩频通信方式。对于直扩信号侦察,首先要对直扩信号的存在进行检测,然后估计出直扩信号的载频、伪码周期、码速率以及伪码序列等重要参数,以便能够获取原始的信息码或者对其进行各种干扰。在针对信号检测以及对直扩通信的参数估计上面,本文主要研究了平方倍频法、延时相乘检测算法、循环谱切片法、以及相关二阶矩和二次功率谱法等算法来检测直接序列扩频信号的存在时,并估计出了直扩信号的载频(平方倍频法、循环谱切片法)、伪码码速率(延时相乘算法、循环谱切片法)、伪码周期(相关二阶矩、二次功率谱法),针对不同算法,在验证了算法对于参数估计和检测的有效性的基础上,然后进行了性能分析。在伪码序列估计问题上,采用了最大似然估计法和小波神经网络两种算法。针对最大似然估计方法,利用迭代的思想,大大简化了最大似然估计的计算过程。而在利用神经网络估计伪码序列时,利用小波神经元来改进了传统的神经网络,加强了神经网络的抗噪声性能,使得在低信噪比条件下,伪码的估计性能得到了提高。最后对于周期长码直扩信号,借鉴短码估计的知识,采用了一种分段的最大似然估计算法来估计伪码序列,并对算法的的功能进行了验证和性能分析。
[Abstract]:Spread spectrum communication has been widely used in both military and civil fields because of its advantages such as wide bandwidth, low detection probability and strong anti-jamming ability. Direct sequence spread spectrum communication is a common spread spectrum communication mode in spread spectrum communication system. For the detection of DSSS signals, the existence of DSSS signals is first detected, and then the carrier frequency, pseudo-code period, code rate and pseudo-code sequence of DSSS signals are estimated. In order to obtain the original information code or interfere with it. On the basis of signal detection and parameter estimation of DSSS communication, this paper mainly studies the squared frequency doubling method, the delay multiplication detection algorithm, the cyclic spectrum slice method. When detecting the existence of direct sequence spread spectrum signal by correlation second-order moment and quadratic power spectrum method, the carrier frequency (squared doubling method, cyclic spectrum slice method) and pseudo-code rate (delay multiplication algorithm) of direct sequence spread spectrum signal are estimated. Cyclic spectrum slicing method, pseudo-code period (correlation second-order moment, quadratic power spectrum method), for different algorithms, the effectiveness of the algorithm for parameter estimation and detection is verified, and then the performance analysis is carried out. In the problem of pseudo code sequence estimation, two algorithms, maximum likelihood estimation and wavelet neural network, are used. For the maximum likelihood estimation method, the calculation process of the maximum likelihood estimation is greatly simplified by using iterative method. When using neural network to estimate pseudo-code sequence, wavelet neural network is used to improve the traditional neural network, and the anti-noise performance of neural network is enhanced, so that the estimation performance of pseudo-code is improved under the condition of low signal-to-noise ratio (SNR). Finally, a piecewise maximum likelihood estimation algorithm is used to estimate the pseudo code sequence for the period long code DSSS signal, and the function of the algorithm is verified and its performance is analyzed.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN914.42

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