A Sequential L_p-norm Filter for Robust Estimation

机译：用于稳健估计的顺序L_p-范数滤波器

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A novel robust sequential Lp filter is developed in this paper by leveraging the maximum a posteriori estimation theory and using generalised normal distributions to represent both state prediction errors and measurement residuals. The formulation leads to the flexibility of choosing the parameter p for two different types of aforementioned error sources. Numerical simulations are given for a nonlinear ground tracking scenario, with measurements corrupted with outliers. Results indicate the new Lp -norm filter presents robustness to filter initialisation errors and measurement outliers and outperforms a standard unscented Kalman filters and the Huber unscented Kalman filter in terms of error statistics.

机译：通过利用最大后验估计理论并使用广义正态分布来表示状态预测误差和测量残差，本文开发了一种新颖的鲁棒时序Lp滤波器。该公式导致针对两种不同类型的上述误差源选择参数p的灵活性。给出了针对非线性地面跟踪情况的数值模拟，其测量值被异常值所破坏。结果表明，新的Lp范数滤波器具有强大的鲁棒性，可以过滤初始化误差和测量异常值，并且在误差统计方面优于标准的无味Kalman滤波器和Huber无味Kalman滤波器。

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《International Conference on Information Fusion》|2020年|1-5|共5页
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Yang Yang;
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Pollution measurement; Robustness; Estimation; Measurement uncertainty; Kalman filters; Gaussian distribution; Error analysis;

机译：污染测量;稳健性;估计;测量不确定度;卡尔曼滤波;高斯分布;误差分析;

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1. Nonlinear filtering for sequential spacecraft attitude estimation with real data: Cubature Kalman Filter, Unscented Kalman Filter and Extended Kalman Filter [J] . Garcia R. V., Pardal P. C. P. M., Kuga H. K., Advances in space research . 2019,第2期

机译：用于使用实际数据进行连续航天器姿态估计的非线性滤波：Cubature Kalman滤波，Unscented Kalman滤波和Extended Kalman滤波
2. Nonlinear filtering for sequential spacecraft attitude estimation with real data: Cubature Kalman Filter, Unscented Kalman Filter and Extended Kalman Filter [J] . Garcia R. V., Pardal P. C. P. M., Kuga H. K., Journal of neurosurgical sciences . 2019,第2期

机译：具有真实数据的连续航天器姿态估计的非线性滤波：Cubature Kalman滤波器，Unscented Kalman滤波器和扩展卡尔曼滤波器
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机译：l_p-范数用于图像识别的最佳滤波器。第一部分算法
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机译：基于L_P-NOM的鲁棒扩散递归自适应滤波算法
5. Sequential Monte Carlo particle filtering for state estimation. [D] . Smith, Laurence. 2006

机译：顺序蒙特卡洛粒子滤波用于状态估计。
6. Robust Scale Adaptive Tracking by Combining Correlation Filters with Sequential Monte Carlo [O] . Junkai Ma, Haibo Luo, Bin Hui, 2017

机译：通过将相关滤波器与顺序蒙特卡洛相结合的鲁棒尺度自适应跟踪
7. Crf-filters: Discriminative particle filters for sequential state estimation [O] . Benson Limketkai, Dieter Fox, Lin Liao 2007

机译：Crf-filters：区分粒子滤波器，用于顺序状态估计

A Sequential L_p-norm Filter for Robust Estimation

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