基于相关-循环谱方法的DSSS／BPSK信号检测与识别

在通信侦察、频谱监测等非协作通信领域,直接序列扩频(Direct Sequence Spread Spectrum,DSSS)信号得到广泛应用。但其低功率谱密度发射的隐蔽性,抗干扰能力强等特点增加了通信对抗中信号截获、检测和分析的难度。低信噪比情况下,针对DSSS/BPSK信号与同调制类型窄带BPSK信号的辨别问题,利用直扩信号的循环平稳性、扩频序列的周期性和良好的自相关性,给出相关-循环谱算法,进行直扩信号的检测识别。对该算法进行了仿真实验,并与相关积累法和倒谱法比较,实验结果说明该算法具有更低的信噪比容限和更高的检测识别正确率。

Detection and Identification of DSSS/BPSK Signal Based on Autocorrelation-Cyclic Spectrum Algorithm

In non-cooperation communication system such as communication reconnaissance and spectrum surveillance, the direct sequence spread spectrum (DSSS) signal is widely used for its characteristics of low power spectrum and anti-interference. In communication countermeasure, DSSS signal is more difficult to intercept, detect and analyze. An algorithm of autocorrelation-cyclic spectrum, based on characteristics of DSSS's cyclo-stationarity, the spread sequence's periodicity and autocorrelation, is proposed to solve the problem of detection and recognition of DSSS/BPSK and narrowband BPSK in lower SNR condition. The computer simulation and experimental results demonstrate that the algorithm is effective.