[PDF][PDF] 基于概率假设密度滤波方法的多目标跟踪技术综述

杨峰, 王永齐, 梁彦, 潘泉 - 自动化学报, 2013 - aas.net.cn
摘要概率假设密度(Probability hypothesis density, PHD) 滤波方法在多目标跟踪, 交通管制,
图像处理以及多传感器管理等领域得到了广泛关注. 本文对基于PHD 滤波方法的多目标跟踪 …

A particle dyeing approach for track continuity for the SMC-PHD filter

T Li, S Sun, JM Corchado… - … Conference on Information …, 2014 - ieeexplore.ieee.org
This paper proposes a novel particle labeling (termed asdyeing ‚) method for track continuity
for the sequential Monte Carlo (SMC) implementation of the probability hypothesis density …

Fusion-based multidetection multitarget tracking with random finite sets

L Gao, G Battistelli, L Chisci… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Multidetection (MD) systems are characterized by multiple observation modes (OMs), and
hence, simultaneously produce multiple measurements for each target. The key challenge in …

Robust multisensor multitarget tracker with application to passive multistatic radar tracking

G Battistelli, L Chisci, S Morrocchi… - … on Aerospace and …, 2012 - ieeexplore.ieee.org
This paper presents a novel approach to multitarget multisensor tracking, based on the
combination of a probability hypothesis density (PHD) smoother and hard multisensor …

[PDF][PDF] 一种非线性GM-PHD 滤波新方法

王品, 谢维信, 刘宗香, 李鹏飞 - 电子学报, 2023 - ejournal.org.cn
为了解决目标数未知情况下的多目标跟踪问题, 提出了一种非线性条件下的高斯混合概率假设
密度滤波新方法. 该方法利用三阶球面容积-径向采样规则计算目标状态的概率分布特性 …

Multi-target state-estimation technique for the particle probability hypothesis density filter

LK Lin, H Xu, WD Sheng, W An - Science China Information Sciences, 2012 - Springer
A simple yet effective state-estimation algorithm is presented and demonstrated to have
advantages over previous standard clustering techniques used for the particle probability …

A robust fast LMB filter for superpositional sensors

G Li, P Wei, Y Li, L Gao, H Zhang - Signal Processing, 2020 - Elsevier
This paper aims to deal with the problem of multitarget tracking based on superpositional
sensors, while the measurement noise is unknown. To this end, the labeled multi-Bernoulli …

Optimal flow models for multiscan data association

G Battistelli, L Chisci, F Papi, A Benavoli… - … on Aerospace and …, 2011 - ieeexplore.ieee.org
Multiscan data association can significantly enhance tracking performance in critical radar
surveillance scenarios involving multiple targets, low detection probability, high false alarm …

[图书][B] Target Tracking with Random Finite Sets

W Wu, H Sun, M Zheng, W Huang - 2023 - Springer
In the process of research on target tracking and information fusion, the authors were deeply
impressed by the great influence of the random finite set (RFS) theory. As a scientific top …

基于全局时空信息的SMC-PHD 多目标跟踪算法

杨峰, 王永齐, 梁彦, 潘泉 - 信息与控制, 2014 - xk.sia.cn
为了实现多目标峰值及航迹联合提取, 提出了一种基于全局时空信息的序贯蒙特卡洛概率假设
密度(SMC-PHD) 多目标峰值提取及航迹提取一体化处理方法. 该算法利用粒子空间分布信息将 …