Sequential Monte Carlo methods for multi-aircraft trajectory prediction in air traffic management

DOI10.1002/acs.1174zbMath1202.90069OpenAlexW2085021215MaRDI QIDQ3064299

John Lygeros, I. Lymperopoulos

Publication date: 21 December 2010

Published in: International Journal of Adaptive Control and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/acs.1174

zbMATH Keywords

curse of dimensionalityair trafficsequential Monte Carloparticle filtertrajectory prediction

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Applications of statistics in engineering and industry; control charts (62P30) Filtering in stochastic control theory (93E11) Monte Carlo methods (65C05) Traffic problems in operations research (90B20)

Related Items (5)

Error analysis of stochastic flight trajectory prediction models ⋮ Numerical fitting‐based likelihood calculation to speed up the particle filter ⋮ Collision avoidance command governor for multi-vehicle unmanned systems ⋮ Sequential Monte Carlo methods for multi-aircraft trajectory prediction in air traffic management ⋮ Simulation-based Bayesian optimal design of aircraft trajectories for air traffic management

Cites Work

• Sequential Monte Carlo Methods in Practice
• Sequential Monte Carlo methods for multi-aircraft trajectory prediction in air traffic management
• Rao-Blackwellisation of sampling schemes
• Trajectory Synthesis for Air Traffic Automation
• A sequential particle filter method for static models
• Filtering via Simulation: Auxiliary Particle Filters
• Bayesian Inference in Econometric Models Using Monte Carlo Integration
• A survey of convergence results on particle filtering methods for practitioners
• Marginalized particle filters for mixed linear/nonlinear state-space models

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