A Labeled GM-PHD Filter for Explicitly Tracking Multiple Targets [PDF]
Sensors, 2021 In this study, an explicit track continuity algorithm is proposed for multitarget tracking (MTT) based on the Gaussian mixture (GM) implementation of the probability hypothesis density (PHD) filter. Trajectory maintenance and multitarget state extraction
Yiyue Gao +3 more
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Label GM-PHD Filter Based on Threshold Separation Clustering [PDF]
Sensors, 2021 Gaussian mixture probability hypothesis density (GM-PHD) filtering based on random finite set (RFS) is an effective method to deal with multi-target tracking (MTT).
Kuiwu Wang, Qin Zhang, Xiaolong Hu
doaj +6 more sources
An Unbalanced Weighted Sequential Fusing Multi-Sensor GM-PHD Algorithm [PDF]
Sensors, 2019 In this paper, we study the multi-sensor multi-target tracking problem in the formulation of random finite sets. The Gaussian Mixture probability hypothesis density (GM-PHD) method is employed to formulate the sequential fusing multi-sensor GM-PHD (SFMGM-
Han Shen-Tu +4 more
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Multi-Feature Matching GM-PHD Filter for Radar Multi-Target Tracking [PDF]
Sensors, 2022 Multi-target tracking (MTT) is one of the most important functions of radar systems. Traditional multi-target tracking methods based on data association convert multi-target tracking problems into single-target tracking problems.
Jin Tao +5 more
doaj +4 more sources
Extended emitter target tracking using GM-PHD filter. [PDF]
PLoS ONE, 2014 If equipped with several radar emitters, a target will produce more than one measurement per time step and is denoted as an extended target. However, due to the requirement of all possible measurement set partitions, the exact probability hypothesis ...
Youqing Zhu +4 more
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Tracking Multiple Video Targets with an Improved GM-PHD Tracker [PDF]
Sensors, 2015 Tracking multiple moving targets from a video plays an important role in many vision-based robotic applications. In this paper, we propose an improved Gaussian mixture probability hypothesis density (GM-PHD) tracker with weight penalization to ...
Xiaolong Zhou +3 more
doaj +8 more sources
Improved Bearings-Only Multi-Target Tracking with GM-PHD Filtering [PDF]
Sensors, 2016 In this paper, an improved nonlinear Gaussian mixture probability hypothesis density (GM-PHD) filter is proposed to address bearings-only measurements in multi-target tracking.
Qian Zhang, Taek Lyul Song
doaj +7 more sources
Advancing ADAS Perception: A Sensor-Parameterized Implementation of the GM-PHD Filter [PDF]
SensorsModern vehicles equipped with Advanced Driver Assistance Systems (ADAS) rely heavily on sensor fusion to achieve a comprehensive understanding of their surrounding environment.
Christian Bader, Volker Schwieger
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Multisensor Multi-Target Tracking Based on GM-PHD Using Out-Of-Sequence Measurements [PDF]
Sensors, 2019 In this paper, we study the issue of out-of-sequence measurement (OOSM) in a multi-target scenario to improve tracking performance. The OOSM is very common in tracking systems, and it would result in performance degradation if we used it inappropriately.
Meiqin Liu +3 more
doaj +2 more sources
The Labeled Square Root Cubature Information GM-PHD Approach for Multi Extended Targets Tracking [PDF]
SensorsFor modern radars with high resolutions, an extended target may generate more than one observations. The conventional point target-based tracking method can hardly be applied in such scenarios.
Zhe Liu +4 more
doaj +2 more sources