Adaptively Random Weighted Cubature Kalman Filter for Nonlinear Systems

Gao Zhaohui; Mu Dejun; Zhong Yongmin; Gu Chengfan; Ren Chengcai

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Adaptively Random Weighted Cubature Kalman Filter for Nonlinear Systems

机译：非线性系统的自适应随机加权Cubature卡尔曼滤波

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This paper presents a new adaptive random weighting cubature Kalman filtering method for nonlinear state estimation. This method adopts the concept of random weighting to address the problem that the cubature Kalman filter (CKF) performance is sensitive to system noise. It establishes random weighting theories to estimate system noise statistics and predicted state and measurement together with their associated covariances. Subsequently, it adaptively adjusts the weights of cubature points based on the random weighting estimations to improve the prediction accuracy, thus restraining the disturbances of system noises on state estimation. Simulations and comparison analysis demonstrate the improved performance of the proposed method for nonlinear state estimation.

机译：提出了一种用于非线性状态估计的自适应自适应加权加权卡尔曼滤波新方法。该方法采用随机加权的概念来解决库曼卡尔曼滤波器（CKF）性能对系统噪声敏感的问题。它建立了随机加权理论，以估计系统噪声统计数据，预测状态和测量以及相关的协方差。随后，它基于随机加权估计自适应地调整孵化点的权重，以提高预测精度，从而在状态估计中抑制系统噪声的干扰。仿真和比较分析证明了所提出的非线性状态估计方法的改进性能。

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《Mathematical Problems in Engineering》 |2019年第2期|4160847.1-4160847.13|共13页
作者
Gao Zhaohui; Mu Dejun; Zhong Yongmin; Gu Chengfan; Ren Chengcai;
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Northwestern Polytech Univ Sch Automat Xian 710072 Shaanxi Peoples R China;

RMIT Univ Sch Engn Melbourne Vic 3083 Australia;

Univ Melbourne Dept Mech Engn Melbourne Vic 3010 Australia;

Baicheng Ordnance Test Ctr China Baicheng 137001 Peoples R China;

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1. Adaptively Random Weighted Cubature Kalman Filter for Nonlinear Systems [J] . Zhaohui Gao, Dejun Mu, Yongmin Zhong, Mathematical Problems in Engineering: Theory, Methods and Applications . 2019,第1期

机译：非线性系统的自适应随机加权Cucature Kalman滤波器
2. Hypersonic entry vehicle state estimation using nonlinearity-based adaptive cubature Kalman filters [J] . Sun Tao, Xin Ming Acta astronautica . 2017,第MAY期

机译：基于非线性的自适应库曼卡尔曼滤波器的高超音速进入车辆状态估计
3. 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
4. Distributed weighted averaging-based robust Cubature Kalman Filter for state estimation of nonlinear systems in wireless sensor networks [C] . Behrouz Safarinejadian, Foroogh Mohammadnia International conference on computer and knowledge engineering . 2016

机译：基于分布加权平均的鲁棒Cubature卡尔曼滤波器用于无线传感器网络中非线性系统的状态估计
5. Sampled-data Kalman filtering and multiple model adaptive estimation for infinite-dimensional continuous-time systems. [D] . Sallberg, Scott A. 2007

机译：无限维连续时间系统的采样数据卡尔曼滤波和多模型自适应估计。
6. Input Forces Estimation for Nonlinear Systems by Applying a Square-Root Cubature Kalman Filter [O] . Xuegang Song, Yuexin Zhang, Dakai Liang 2017

机译：应用平方根Courture卡尔曼滤波的非线性系统输入力估计
7. Adaptively Random Weighted Cubature Kalman Filter for Nonlinear Systems [O] . Zhaohui Gao, Dejun Mu, Yongmin Zhong, 2019

机译：非线性系统的自适应随机加权Cucature Kalman滤波器

Adaptively Random Weighted Cubature Kalman Filter for Nonlinear Systems

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