Extended Object Tracking with Random Hypersurface Models
Systems and Control
2013-04-19 v1
Abstract
The Random Hypersurface Model (RHM) is introduced that allows for estimating a shape approximation of an extended object in addition to its kinematic state. An RHM represents the spatial extent by means of randomly scaled versions of the shape boundary. In doing so, the shape parameters and the measurements are related via a measurement equation that serves as the basis for a Gaussian state estimator. Specific estimators are derived for elliptic and star-convex shapes.
Cite
@article{arxiv.1304.5084,
title = {Extended Object Tracking with Random Hypersurface Models},
author = {Marcus Baum and Uwe D. Hanebeck},
journal= {arXiv preprint arXiv:1304.5084},
year = {2013}
}
Comments
Draft accepted for publication in IEEE Transactions on Aerospace and Electronic Systems