风险敏感粒子滤波器的替代配方(后验)

S. Bhaumik, S. Sadhu, T. Ghoshal
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引用次数: 9

摘要

提出了一种非线性非高斯系统的后验风险敏感粒子滤波算法。针对高斯线性测量情况和非线性高斯测量情况,导出了风险敏感粒子滤波器的线性化最优方案。讨论了扩展风险敏感滤波器(ERSF)、中心差分风险敏感滤波器(CDRSF)等非线性风险敏感滤波器作为风险敏感粒子滤波器的适用性。该滤波器应用于高度非线性高斯系统。结果显示了扩展风险敏感滤波器(ERSF),后验风险敏感粒子滤波器(RSPF)和自适应网格风险敏感滤波器(AGRSF)在代表性运行中的性能比较。给出了该滤波器的均方根误差(RMSE),并与ERSF和AGRSF进行了比较。研究了所提风险敏感估计器的计算代价,并与其他非线性风险敏感滤波器进行了比较
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Alternative Formulation of Risk-Sensitive Particle Filter (Posterior)
An algorithm for posterior risk-sensitive particle filter for nonlinear non-Gaussian system has been proposed in this paper. For Gaussian linear measurement case optimal proposal and for nonlinear Gaussian measurement case linearized version of optimal proposal for risk-sensitive particle filter is derived. The applicability of nonlinear risk-sensitive filters such as extended risk-sensitive filter (ERSF), central difference risk-sensitive filter (CDRSF) as a proposal for risk-sensitive particle filter is discussed. The proposed filter is applied to a highly nonlinear Gaussian system. Results are provided to show the comparative performance of extended risk-sensitive filter (ERSF), posterior risk-sensitive particle filter (RSPF) and adaptive grid risk-sensitive filter (AGRSF) for a representative run. Root mean square error (RMSE) of the proposed filter has also been provided and compared with ERSF and AGRSF. The computational cost of the proposed risk-sensitive estimator is studied and compared with other nonlinear risk-sensitive filters
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