We review some advances of the particle filtering (PF) algorithm that have been achieved in
the last decade in the context of target tracking, with regard to either a single target or …

摘要本文梳理了粒子滤波理论基本内容, 发展脉络和最新研究进展, 特别是对其在多目标跟踪
应用中的一系列难点问题与主流解决思路进行了详细分析和报道. 常规粒子滤波研究重点主要 …

The particle filtering algorithm was introduced in the 1990s as a numerical solution to the
Bayesian estimation problem for nonlinear and non-Gaussian systems and has been …

Resampling is a critical procedure that is of both theoretical and practical significance for
efficient implementation of the particle filter. To gain an insight of the resampling process …

The prior covariance estimation method based on inverse covariance intersection (ICI) is
proposed to apply the particle flow filter. The proposed method has better estimate …

We consider convergence properties of particle filters with Gaussian importance
distributions for certain time-varying Poisson regression models. We analyze both the …

摘要针对传统粒子滤波定位算法在粒子的更新中仅考虑当前里程信息, 论文基于KLD-
粒子滤波算法实时跟踪每次迭代所需粒子数, 提出了一个KLD 粒子滤波定位改进算法 …

In this paper, the proposed method replaces a linear transformation step in an ensemble
transform particle filter (ETPF) with an algorithm based on regularized optimal transport …

A resampling method is presented for improving the performance of particle filters by using
adaptive numbers of the resampling particles. The proposed method replaces the …

We analyze the L p-convergence of a previously proposed Girsanov theorem based particle
filter for discretely observed stochastic differential equation (SDE) models. We prove the …