【作者】 李懿；

【导师】 李锋；

【作者基本信息】 江苏科技大学 ， 信号与信息处理， 2011， 硕士

【摘要】 扩频通信由于具有抗干扰能力强、截获率低、良好的码分多址能力等优点,被广泛地应用于移动通信、雷达、导航和定位等领域。在通信侦察和频谱监测等非协作通信领域中,由于信噪比低和先验知识条件缺乏,以至直接序列扩频信号的检测与参数估计难于实现,使之成为当前这一领域中的重要研究课题。由于直接序列扩频信号的带宽远大于基带信号带宽,能量分布于更宽的频带,且功率谱密度很低,以至于通常淹没在噪声中。正是由于这些特点使得直接序列扩频信号难于检测,且在伪随机序列未知的前提下,即使检测到了也难以恢复待传输的信息,导致常规处理方法在此情况下将失效。目前,对于直接序列扩频信号的检测和参数估计已有一些方法,这些方法对于单一参数具有良好的检测结果,但在低信噪比情况下性能趋于恶化。本文主要研究了时域相关检测、延时相乘、相关累积、循环谱检测等方法,在归纳前人理论的基础上,采用了改进方法,主要研究成果如下:1.在直扩信号检测及伪码周期的参数估计方面,分析常规时域相关检测方法的基础上,采用了时域相关二阶矩检测方法,对信号进行分段自相关运算,然后均方迭加平均相关数据。此法有效地抑制噪声,实现了在低信噪比的条件下直接序列扩频信号伪码周期的准确估计。2.在延时相乘法的基础上,分析了在相关域上可检测出伪码的周期特性,在频域上可检测出伪码速率和载频参数的特点,并结合自适应噪声抵消器、相关累积方法和频谱校正方法,组成了时域延时相关检测系统。在低信噪比条件下,可实现对直接序列扩频信号的伪码周期、伪码速率和载频的准确估计。3.为实现更低信噪比条件下的直接序列扩频信号检测与参数估计,在循环谱理论的基础上,分析了循环统计量抑制平稳噪声的能力,采用了基于Welch法的集平均循环谱方法,对信号分段使用频域平滑循环周期图算法后,进行迭加平均。此法可有效利用循环谱包络估计出直接序列扩频信号的伪码速率、载频参数。实验证明,以上三种改进方法在低信噪比条件下具有良好的估计效果,对于直接序列扩频信号的盲解扩具有一定的意义。更多还原

【Abstract】 The spread spectrum communication depended on good anti-interference ability, low probability of interception and the advantages of CDMA, was widely used in mobile communication, radar, navigation, orientation and other fields. In the area of non-cooperative communication such as communication reconnaissance and spectrum monitoring, owing to low SNR and lacking of priori knowledge, direct sequence spread spectrum(DSSS) signal detection and parameters estimation were difficult to achieve those have become an important issue.Since the bandwidth of DSSS signal was much larger than the bandwidth of baseband signal, thus energy of DSSS signal was distributed in the much wider bandwidth, power spectrum density was very low so as to submerge in the noise. These features made DSSS signal difficult to detect, or it was difficult to restore the information which was transmitted in the premise of the unknown pseudo-random(PN) sequence. This made the conventional approach invalid at low SNR. At present, there had been some methods for DSSS signal detection and parameters estimation. These methods were good for test results of single parameters. However, for DSSS signal, detection performance tended to deteriorate at low SNR.In this dissertation, time-domain correlation detection, delay-multiply, correlation cumulation, cyclic spectrum and other methods were considered. On the base of predecessors’studies, the improved methods were presented here.1. In the dissertation, in order to detect DSSS signal and estimate the period of PN, time-domain second-order moment detection was proposed based on time-domain correlation detection. The DSSS signal was cut up into several segments in this method, their correlation functions were obtained, and then the mean for superposition of square of correlation data was calculated. This method is able to suppress the additive white Gaussian noise so as to achieve an accurate estimation of the period of PN at low SNR.2. Based on delay-multiply detection, it indicated that the period of PN showed on the correlation domain, in addition, chip rate and carrier frequency displayed on the frequency domain. This method combined the formers with adaptive noise cancellation, correlation cumulation and spectrum correction in order to compose a detection system of time-domain delay correlation. It can estimate the period of PN, chip rate and carrier frequency accurately.3. In order to achieve DSSS signal detection and parameters estimation at lower SNR, cyclic statistics had the ability to suppress stationary noise based on cyclic spectrum theory. Improved set-average cyclic spectrum based on Welch method was proposed in this paper. DSSS signal that was divided into several sections used frequency smoothed cyclic periodogram algorithm, then the results for computing the mean were added up. This method used the envelope of cyclic spectrum to estimate the chip rate and carrier frequency, and it had high accuracy.The simulation showed that the aboved methods can achieve high precision at the low SNR in non-cooperative communication, and had important significance for blind despreading.更多还原