粒子滤波和ANFIS级联滤波的去噪技术
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国家自然科学基金资助项目(51175535;60907041);重庆市科委国际合作类攻关项目(2011GZ0017);重庆市自然科学基金重点资助项目(CSTC,2012jjB4003);重庆市教委科研基金资助项目(KJ110507)


Denoising technique based on cascaded filtering of particle filter and ANFIS
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    摘要:

    为实现实际应用中的非线性、非高斯系统中的状态估计,结合粒子滤波非线性估计的优势和自适应神经模糊推理系统(ANFIS)的非线性逼近功能,建立了ANFIS粒子滤波模型。该模型首先通过ANFIS消除测量信号中有色噪声的影响,再运用粒子滤波实现对状态的最优估计,从而进一步提高估计精度。仿真结果表明ANFIS与PF的级联滤波较单一的粒子滤波均值减少了65%,方差减小了74.4%。ANFIS粒子滤波对于强非线性系统的噪声消除效果显著,使状态估计精度得到了较大提高,证明了该级联滤波模型的有效性。

    Abstract:

    For the practical application of nonlinear, non-Gaussian noise system state estimation,this paper develops the ANFIS- Particle filter cascaded filtering model based on the adaptive neuro-fuzzy inference system(ANFIS) nonlinear approximation function and particle filter’s obvious advantages for non-linear state estimation. ANFIS is used to eliminate the bias in the colored noise of the signal, then the filtered signal is processed by the particle filter to realize the optimal state estimation. The simulation results demonstrate that with the cascade filter model the mean and variance are reduced by 65% and 74% respectively, ANFIS-particle filter model has significant noise cancellation effect for strongly nonlinear systems, and the state estimation accuracy has been greatly enhanced, which verifies the effectiveness of the proposed model.

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刘宇,曾燎燎,路永乐,黎蕾蕾,潘英俊.粒子滤波和ANFIS级联滤波的去噪技术[J].重庆大学学报,2012,35(4):72-76.

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