Results 21 to 30 of about 175,081 (248)
Multi-Sensor Multi-Target Tracking Using Probability Hypothesis Density Filter
IEEE Access, 2019 Compared with the single sensor tracking system, the multi-sensor tracking system has several advantages in target tracking, such as a larger field of view and higher tracking accuracy.
Long Liu +3 more
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Multisensor Vehicle Tracking with the Probability Hypothesis Density Filter [PDF]
2006 9th International Conference on Information Fusion, 2006 In this contribution we apply the probability hypothesis density (PHD) filter algorithm for joint tracking of an unknown varying number of targets to automotive environment sensing systems. We use data from a vision and a lidar sensor as well as the vehicle ESP system.
Mirko Mählisch +3 more
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Applied Sciences, 2017 Underwater multi-targets tracking has always been a difficult problem in active sonar tracking systems. In order to estimate the parameters of time-varying multi-targets moving in underwater environments, based on the Bayesian filtering framework, the ...
Xiao Chen, Yaan Li, Yuxing Li, Jing Yu
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Active Sonar Target Tracking Based on the GM-CPHD Filter Algorithm [PDF]
Xibei Gongye Daxue Xuebao, 2018 The estimation of underwater multi-target state has always been the difficult problem of active sonar target tracking.In order to get the variable number of target and their state, the random finite set theory is applied to multi-target tracking system ...
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A shrinkage probability hypothesis density filter for multitarget tracking [PDF]
EURASIP Journal on Advances in Signal Processing, 2011 22 ...
Huisi Tong +3 more
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IET Radar, Sonar & Navigation, 2022 Non‐cooperative bistatic radar refers to the passive bistatic radar using a non‐cooperative radar as the illuminator of opportunity. Limited by the non‐cooperation and bistatic configuration, multi‐target tracking of the non‐cooperative bistatic radar is
Sen Wang, Qinglong Bao, Jiameng Pan
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IEEE Access, 2020 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
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Box-Particle Implementation and Comparison of Cardinalized Probability Hypothesis Density Filter [PDF]
Radioengineering, 2016 This paper develops a box-particle implementation of cardinalized probability hypothesis density filter to track multiple targets and estimate the unknown number of targets.
L. Song, M. Liang, H. Ji
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IEEE Access, 2019 In multi-extended target tracking, each target may generate more than one observation. The traditional probability hypothesis density (PHD)-based methods are no longer effective in such scenarios.
Zhe Liu +5 more
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Gaussian Mixture Probability Hypothesis Density Filter for Heterogeneous Multi-Sensor Registration
MathematicsSpatial registration is a prerequisite for data fusion. Existing methods primarily focus on similar sensor scenarios and rely on accurate data association assumptions. To address the heterogeneous sensor registration in complex data association scenarios,
Yajun Zeng +5 more
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