期刊
SENSORS
卷 17, 期 12, 页码 -出版社
MDPI
DOI: 10.3390/s17122707
关键词
particle filter; target tracking; nonlinear filter; Monte Carlo sampling; Bayesian inference
资金
- Marie Sklodowska-Curie Individual Fellowship [709267]
- National Natural Science Foundation of China [51775435]
- Marie Curie Actions (MSCA) [709267] Funding Source: Marie Curie Actions (MSCA)
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 multiple targets in the presence of false or missing data. The first part of our review is on remarkable achievements that have been made for the single-target PF from several aspects including importance proposal, computing efficiency, particle degeneracy/impoverishment and constrained/multi-modal systems. The second part of our review is on analyzing the intractable challenges raised within the general multitarget (multi-sensor) tracking due to random target birth and termination, false alarm, misdetection, measurement-to-track (M2T) uncertainty and track uncertainty. The mainstream multitarget PF approaches consist of two main classes, one based on M2T association approaches and the other not such as the finite set statistics-based PF. In either case, significant challenges remain due to unknown tracking scenarios and integrated tracking management.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据