混沌多进制直接序列扩频信号的盲解扩

Chaotic M-ary direct sequence spread spectrum signals blind despreading

为了在混沌扩频序列未知的情况下实现混沌多进制直接序列扩频信号的盲解扩,提出了一种盲解扩方法。该方法将混沌多进制扩频信号分段,借鉴数据挖掘领域的K均值聚类算法,对分段数据按照最小簇内距离、最大簇间距离的原则分类,通过平均侧影宽度完成对延迟时间和扩频序列数量的估计。对于单用户、窄带干扰以及多用户情况,进行了数值仿真。结果表明:该方法适用于混沌多进制扩频信号的盲解扩问题。

A blind despreading method was developed to blindly despread chaotic multi-sequence direct sequence spread spectrum （DSSS） signals with unknown spreading codes. The chaotic M-ary DSSS signal was first divided into non-overlapped individuals. The K-means clustering method used in data mining was used to estimate the clustering properties spreading codes by maximizing the inter-cluster distances and minimizing the inner-cluster distances. The delay time and the number of spreading codes were estimated by maximizing the average silhouette width. Simulations were used to model the blind despreading performance for a single user with narrow band interference and multiple users. The results show the feasibility of this method to blindly despread chaotic M-ary DSSS signal.