Results 31 to 40 of about 5,063,949 (192)
Under the Gaussian noise assumption, the probability hypothesis density (PHD) filter represents a promising tool for tracking a group of moving targets with a time-varying number.
Weijun Xu
doaj +1 more source
The existing Probability Hypothesis Density (PHD) filters with birth intensity estimation only operate on single or two consecutive scan data for multi-target tracking.
Qian Zhu +3 more
doaj +1 more source
The key challenge for multiple vessel cooperative localization is considered as data association, in which state-of-the-art approaches adopt a divide-and-conquer strategy to acquire measurement-to-target association.
Feihu Zhang +3 more
doaj +1 more source
Multitarget Tracking Using One Time Step Lagged Delta-Generalized Labeled Multi-Bernoulli Smoothing
Aiming at improving the tracking performance of the delta-generalized labeled multi-Bernoulli (δ-GLMB) filter, we present a one time step lagged δ-GLMB smoother in this work, which also inherently outputs targets trajectories and differs ...
Guolong Liang +3 more
doaj +1 more source
Assuming that the measurement and process noise covariances are known, the probability hypothesis density (PHD) filter is effective in real-time multi-target tracking; however, noise covariance is often unknown and time-varying for an actual scene.
Zhentao Hu +4 more
doaj +1 more source
Box-particle probability hypothesis density filtering [PDF]
This paper develops a novel approach for multitarget tracking, called box-particle probability hypothesis density filter (box-PHD filter). The approach is able to track multiple targets and estimates the unknown number of targets.
Gning, Amadou +10 more
core +4 more sources
A convolution particle filtering approach for tracking elliptical extended objects [PDF]
This paper proposes a convolution particle filtering approach for extended object tracking. Convolution particle filters (CPFs) are likelihood free filters. They are based on convolution kernel probability density representation.
Gning, Amadou +3 more
core +2 more sources
An Adaptive PHD Filter for Multitarget Tracking with Multispectral Data Fusion
In order to improve the detection and tracking performance of multiple targets from IR multispectral image sequences, the approach based on spectral fusion algorithm and adaptive probability hypothesis density (PHD) filter is proposed.
Guoliang Zhang, Chunling Yang, Yan Zhang
doaj +1 more source
Space Target Tracking with the HRRP Characteristic-Aided Filter via Space-Based Radar
Approaching space target tracking is a typical and challenging mission in the space situational awareness (SSA) field. As the space-based radar is able to monitor the space targets of interest full-weather all-time, the space-based radar system is ...
Shuyu Zheng +4 more
doaj +1 more source
Fluorescent BODIPY‐conjugated thiosemicarbazone ligands and their Ga(III), In(III), and Fe(III) complexes, inspired by Triapine, are developed as theranostic agents. Multiphoton FLIM and confocal microscopy in cancer cells and zebrafish reveal real‐time uptake, mitochondrial localisation, and whilst spectroscopic assays indicated preserved complex ...
Megan J. Green +15 more
wiley +1 more source

