Results 31 to 40 of about 1,207 (171)
Gaussian Process Gaussian Mixture PHD Filter for 3D Multiple Extended Target Tracking
Remote Sensing, 2023 This paper addresses the problem of tracking multiple extended targets in three-dimensional space. We propose the Gaussian process Gaussian mixture probability hypothesis density (GP-PHD) filter, which is capable of tracking multiple extended targets ...
Zhiyuan Yang +4 more
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IEEE Access, 2020 A prior knowledge of the background parameters such as clutter rate and detection profile is of critical importance in the tracking algorithms under the theory of random finite sets for extended objects which would lead to restrictions in the application.
Cuiyun Li, Zehao Fan, Renzheng Shi
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IEEE Access, 2021 When the extension state of the non-ellipsoidal extended target (NET) changes, the performance of traditional multiple target tracking algorithms based on the constant number of sub-objects will decrease.
Yang Gong, Chen Cui, Biao Wu
doaj +1 more source
Genetics Selection Evolution, 2003 A fully Bayesian analysis using Gibbs sampling and data augmentation in a multivariate model of Gaussian, right censored, and grouped Gaussian traits is described.
Madsen Per +5 more
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Generalized Labeled Multi-Bernoulli Extended Target Tracking Based on Gaussian Process Regression
MATEC Web of Conferences, 2018 For the problems that Gamma Gaussian Inverse Wishart Cardinalized Probability Hypothesis Density (GGIW-CPHD) filter cannot accurately estimate the extended target shape and has a bad tracking performance under the condition of low SNR, a new generalized ...
Chi Luo-jia, Feng Xin-xi, Miao Lu
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Random Finite Set-based Extended Target Tracking Method with Amplitude Information
Leida xuebao, 2020 The random finite set-based extended target tracking methods generally partition measurements by spatial information. It is possible to place clutter measurements into target cells in a dense clutter environment resulting in degradation of tracking ...
Chao LIU +3 more
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Adaptive Bayesian Detection for MIMO Radar in Gaussian Clutter
Leida xuebao, 2019 For collocated Multiple-Input Multiple-Output (MIMO) radar, we investigate the target detection problem in Gaussian clutter with an unknown but random covariance matrix.
HAN Jinwang +3 more
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A New Process Uncertainty Robust Student’s t Based Kalman Filter for SINS/GPS Integration
IEEE Access, 2017 Motivated by the problem that the Gaussian assumption of process noise may be violated and the statistics of process noise may be inaccurate when the carrier maneuvers severely, a new process uncertainty robust Student's t-based Kalman filter is proposed
Yulong Huang, Yonggang Zhang
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Remote Sensing, 2023 This paper focuses on the problem of joint detection, tracking, and classification (JDTC) for multiple extended objects (EOs) within a Poisson multi-Bernoulli (MB) mixture (PMBM) filter, where an EO is described as an ellipse, and the ellipse is modeled ...
Yuansheng Li +4 more
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Bayesian Model Averaging in Causal Instrumental Variable Models
Journal of Applied Econometrics, EarlyView.ABSTRACT Instrumental variables are a popular tool to infer causal effects under unobserved confounding, but choosing suitable instruments is challenging in practice. We propose gIVBMA, a Bayesian model averaging procedure that addresses this challenge by averaging across different sets of instrumental variables and covariates in a structural equation ...
Gregor Steiner, Mark Steel
wiley +1 more source