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首页> 外文会议>IEEE International Conference on Acoustics, Speech and Signal Processing >A robust Gaussian approximate filter for nonlinear systems with heavy tailed measurement noises
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A robust Gaussian approximate filter for nonlinear systems with heavy tailed measurement noises

机译：带有重尾量测量噪声的非线性系统的鲁棒高斯近似滤波器

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摘要

The scale matrix and degrees of freedom (dof) parameter of a Student's t distribution are important for nonlinear robust inference, and it is difficult to determine exact values in practical application due to complex environments. To solve this problem, an improved robust Gaussian approximate (GA) filter is derived based on the variational Bayesian approach, where the state together with unknown scale matrix and d-of parameter are inferred. The proposed filter is applied to a target tracking problem with measurement outliers, and its performance is compared with an existing robust GA filter with fixed scale matrix and dof parameter. The results show the efficiency and superiority of the proposed filter as compared with the existing filter.
机译：Student的t分布的比例矩阵和自由度（dof）参数对于非线性鲁棒推断很重要，并且由于复杂的环境在实际应用中很难确定确切的值。为了解决这个问题，基于变分贝叶斯方法推导了一种改进的鲁棒高斯近似（GA）滤波器，该方法可以推断状态，未知比例矩阵和d-of参数。将该滤波器应用于具有测量异常值的目标跟踪问题，并将其性能与现有的具有固定比例矩阵和自由度参数的鲁棒GA滤波器进行了比较。结果表明，与现有滤波器相比，该滤波器具有更高的效率和优越性。

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