Tracking of Merging and Splitting Targets with
Application to Convective Systems
Curtis Storlie Graduate Student with Colorado State University
A statistical approach to target tracking is presented which allows
for birth, death, splitting and merging of targets. Targets are also
allowed to go undetected for several frames. The splitting and
merging of targets is a novel addition for a statistically based
tracking algorithm. This addition is essential for storm tracking,
which is the motivation for this work. The utility of this tracker
extends well beyond the tracking of storms however. It can be
valuable in other tracking applications that have splitting or
merging, such as vortices, radar/sonar signals, or groups of people.
The method assumes that the location of a target behaves like a
Gaussian Process when it is observable. A Markov State Model decides
when the birth, death, splitting, or merging of targets takes place.
The tracking estimate is achieved by an algorithm that finds the paths
that maximize the likelihood of the assumed model. Some theoretical
properties of tracking estimates will also be developed such as
sufficient conditions for consistency. The problem of how to quantify
the confidence in a tracking estimate is addressed as well. The
properties of the proposed method will be demonstrated on simulated
data. Finally, the method is applied to the problem for which it was
designed, tracking storms from radar reflectivity data.