基于辅助模型粒子滤波的混沌信号降噪方法.

In order to solve the problem of that the traditional extended Kalman filter and unscented Kalman filter methods cannot effectively suppress the additive noise of the chaotic system, an improved particle filter algorithm is presented. The state space description of the chaotic system is derived in detail, and a noise reduction method of chaotic signal based on auxiliary sigma point particle filter is proposed. As an example，Lorenz chaotic signal is used to evaluate the efficiency of the proposed algorithm. The results show that the proposed algorithm has obvious effect on noise reduction for Lorenz chaotic signal with noise. [ABSTRACT FROM AUTHOR]