Modified Gaussian Mixture Probability Hypothesis Density Filtering using Clutter Density Estimation for Multiple Target Tracking

Modified Gaussian Mixture Probability Hypothesis Density Filtering using Clutter Density Estimation for Multiple Target Tracking

Gaussian mixture probability hypothesis density (GM-PHD) filtering often assumes a uniform distribution of clutter in the observation area. However, in practice, clutter is often unknown and non-uniform, necessitating accurate estimation of its spatial distribution, non-uniformity, and temporal...

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Bibliographic Details
Main Authors: Lifan Sun, Wenhui Xue, Dan Gao
Format: Article
Language:English
Published: Instituto de Aeronáutica e Espaço (IAE) 2024-04-01
Series:Journal of Aerospace Technology and Management
Subjects:
Gaussian mixture probability hypothesis density
Complex clutter environments
Clutter density estimation
Online Access:https://jatm.com.br/jatm/article/view/1325

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