Gaussian mixture PHD filter for jump Markov models based on best-fitting Gaussian approximation

DOI10.1016/J.SIGPRO.2010.08.004zbMath1217.94054OpenAlexW1997202612MaRDI QIDQ551658

Yingmin Jia, Wen-Ling Li

Publication date: 21 July 2011

Published in: Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.sigpro.2010.08.004

zbMATH Keywords

probability hypothesis density filterbest-fitting Gaussian approximationjump Markov systemmultiple maneuvering targets tracking

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Related Items (2)

GM-PHD Filter With Signal Features Of Emitter ⋮ Extended target shape estimation by fitting B-spline curve

Cites Work

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• Gaussian mixture CPHD filter with gating technique
• Localization of multiple emitters based on the sequential PHD filter
• Tracking and data association
• Analytic Implementations of the Cardinalized Probability Hypothesis Density Filter
• Bayesian Filtering With Random Finite Set Observations
• A Consistent Metric for Performance Evaluation of Multi-Object Filters
• The Gaussian Mixture Probability Hypothesis Density Filter

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