A constrained sensor control method is presented for multiobject tracking using labeled multi-
Bernoulli filters. The proposed framework is based on a novel approximation of the Cauchy …

This paper proposes an efficient implementation of the multi-sensor generalized labeled
multi-Bernoulli (GLMB) filter. The solution exploits the GLMB joint prediction and update …

Abstract The Sequential Monte Carlo (SMC) implementation for the probability hypothesis
density (PHD) filter, referred to as the SMC-PHD filter, is a good candidate for multi-target …

Unmanned aerial vehicles (UAV) are able to achieve autonomous flight without drivers, and
UAV has been a key tool to extract space data. Therefore, how to detect the trajectories of …

This paper proposes efficient implementations for a Generalized Labeled Multi-Bernoulli
filter for a Jump Markov System. The proposed filter operates via combining both prediction …

In Track-Before-Detect (TBD), the aim is to jointly estimate the number of tracks and their
states from low signal-to-noise ratio (SNR) images. This is a challenging problem due to the …

摘要为处理低检测概率情况下目标漏检的情况, 引入一种新的多帧状态估计机制,
提出了一种基于多帧状态估计机制的高斯混合概率假设密度滤波器. 该机制依据不同时间步骤的 …

This paper presents a novel statistical information fusion method to integrate multiple-view
sensor data in multi-object tracking applications. The proposed method overcomes the …

Point pattern data, also known as multiple instance data or bags, are abundant in nature and
applications. However, machine learning problems for point patterns have not received …

This paper presents a solution to the problem of tracking multiple targets from multistatic
Doppler measurements. To the best of our knowledge our solution is the first principled …