Title
Particle filter tracking for banana and contact lens problems
Abstract
In this paper we present an approach for tracking with high-bandwidth radar in long-range scenarios. We consider both two- and three-dimensional measurements in polar and r-u-v, respectively. We show that in these scenarios the extended Kalman filter is not desirable, because it suffers from major consistency problems, and most types of particle filters suffer from a loss of diversity among particles after resampling. This leads to sample impoverishment and divergence of the filter. In the scenarios studied, this loss of diversity can be attributed to the very low process noise. However, a regularized particle filter is shown to avoid this diversity problem while producing consistent results. The regularization is accomplished using a generalized version of the Epanechnikov kernel.
Year
DOI
Venue
2015
10.1109/TAES.2014.130670
IEEE Trans. Aerospace and Electronic Systems
Keywords
Field
DocType
Noise,Kernel,Accuracy,Atmospheric measurements,Particle measurements,Proposals,Radar tracking
Radar,Kernel (linear algebra),Extended Kalman filter,Radar tracker,Control theory,Particle filter,Contact lens,Electronic engineering,Regularization (mathematics),Resampling,Mathematics
Journal
Volume
Issue
ISSN
51
2
0018-9251
Citations 
PageRank 
References 
2
0.40
7
Authors
3
Name
Order
Citations
PageRank
Kevin Romeo120.73
Peter Willett21962224.14
Yaakov Bar-Shalom346099.56