Group Object Structure and State Estimation with Evolving Networks and Monte Carlo Methods
This is the code for the algorithms developed in:
A. Gning, L. Mihaylova, S. Maskell, S. K. Pang, S. Godsill, Group Object Structure and State Estimation with Evolving Networks and Monte Carlo Methods, IEEE Transactions on Signal Processing, Vol. 59, No. 4, April, 1383 - 1396, 2011.
A technique combining sequential Monte Carlo with evolving network is proposed for group object motion tracking. Each group is modelled as a graph which structure changes in time. Each node of
the graph corresponds to a target within the group. The uncertainty of the group structure is estimated jointly with the group target states. New group structure evolving models are proposed for automatic graph structure initialization, incorporation of new nodes, nonexisting nodes removal, and the edge update. Both the state and the graph structure are updated based on range and bearing measurements.
Cite As
Lyudmila Mihaylova (2024). Group Object Structure and State Estimation with Evolving Networks and Monte Carlo Methods (https://www.mathworks.com/matlabcentral/fileexchange/43906-group-object-structure-and-state-estimation-with-evolving-networks-and-monte-carlo-methods), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Platform Compatibility
Windows macOS LinuxCategories
- Control Systems > Control System Toolbox > Control System Design and Tuning > State-Space Control Design and Estimation > State Estimation >
Tags
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Discover Live Editor
Create scripts with code, output, and formatted text in a single executable document.
filters/
graph/
simu_targets_sensors/
work/
Version | Published | Release Notes | |
---|---|---|---|
1.0.0.0 |