Date of Award
Master of Science
Department of Electrical and Computer Engineering
Peter S. Maybeck, PhD
The problem of tracking multiple maneuvering targets in clutter naturally leads to a Gaussian mixture representation of the Provability Density Function (PDF) of the target state vector. State-of-the-art Multiple Hypothesis Tracking (MHT) techniques maintain the mean, covariance and probability weight corresponding to each hypothesis, yet they rely on ad hoc merging and pruning rules to control the growth of hypotheses.
DTIC Accession Number
Williams, Jason L., "Gaussian Mixture Reduction of Tracking Multiple Maneuvering Targets in Clutter" (2003). Theses and Dissertations. 4246.