摘要
针对通信侦察识别中广泛遇到的短波信道下直接序列扩频信号(DSSS)的检测与参数估计问题,提出了一种利用广度优先搜索邻居(BFSN)聚类分析提取未知信号高阶循环累积量循环频率的算法。该算法通过聚类比较截获信号的各类峰值,剔除干扰和奇异类信号,克服了短波信道中常见的多径效应引起的码间串扰(ISI)影响,从而实现了在低信噪比条件下,对直扩信号进行检测和载频的盲估计。对算法进行了理论分析,并通过计算机仿真验证了该算法在低信噪比下具有较好的稳健性。
Aiming at the communication reconnaissance problem of detection and parameter estimation of direct sequence spread spectrum（DSSS） signals in HF Channel,a new algorithm is proposed to extract cyclic frequency of cyclic cumulants by cluster analysis named broad first search neighbors.The algorithm not only can remove the irrelevant and singular signals by comparing the differences of the intercepted signal peaks,but also overecome the ISI effects which is commonly caused by muhipath and attenuation in HF Channel,and thus achieves the detection and carrier frequency blind estimation of DSSS signals in the low SNR conditions.The algorithm is verified by theoretical derivation and simulation experiments,which has higher robust in low SNR conditions.
出处
《科学技术与工程》
北大核心
2014年第29期44-49,共6页
Science Technology and Engineering
基金
国家自然科学基金项目(61102167)资助
关键词
短波信道
直接序列扩频
广度优先搜索
聚类分析
循环累积量
载频估计
HF channel
direct sequence spread spectrum
broad first search
clustering analysis
cyclic cumulants
carrier frequency estimation
