Implicit particle filtering via a bank of nonlinear Kalman filters
Implicit particle filtering via a bank of nonlinear Kalman filters
复制标题
通过一组非线性卡尔曼滤波器进行隐式粒子滤波
DOI：
10.1016/j.automatica.2022.110469
复制
发表时间：
2022
期刊：
影响因子：
6.4
通讯作者：
Fang, Huazhen
中科院分区：
文献类型：
--
作者：
Askari, Iman;Haile, Mulugeta A.;Tu, Xuemin;Fang, Huazhen
隐式粒子滤波器试图通过识别目标分布的高概率区域中的粒子来减轻粒子退化。这项研究的动机是需要提高计算的易处理性，在实施这种方法。我们调查的隐式粒子滤波器中的粒子更新步骤与卡尔曼滤波器的连接，然后制定一个新的实现的隐式粒子滤波器的基础上银行的非线性卡尔曼滤波器。这种实现在计算上更容易接受和有效。
The implicit particle filter seeks to mitigate particle degeneracy by identifying particles in the target distribution’s high-probability regions. This study is motivated by the need to enhance computational tractability in implementing this approach. We investigate the connection of the particle update step in the implicit particle filter with that of the Kalman filter and then formulate a novel realization of the implicit particle filter based on a bank of nonlinear Kalman filters. This realization is more amenable and efficient computationally.