Keywords: 
• 双模型 /
• 无迹卡尔曼滤波 /
• 混沌直扩 /
• 破译

Abstract: In this paper, a dual model unscented Kalman filter chaotic fitting breaking method is proposed to break chaotic direct sequence spread spectrum communication systems in the cases of low spreading factor, low signal-to-noise ratio or severe multipath fading. Based on the characteristic that the range of information symbol is a finite set, the proposed algorithm fits the original chaotic signal through different filters which work in parallel. The fitting errors are used to choose the optimum matching filter, thus to estimate the information symbols. Furthermore, an error-controlling-factor is introduced to increase the distance of model based tracking errors, which can not only facilitate the information extracting process, but also reduce the influence of noise and multipath fading. Theoretical analysis and simulation results prove that the proposed algorithm is superior to the existing breaking method.