Since the early 1990s, significant research has been done on a relatively new algorithm called the Probabilistic MultiHypothesis Tracker (PMHT). The majority of this research has concluded that there are a few weaknesses with this approach to tracking targets in the presence of clutter. First, the number of targets that are being tracked needs to be known a priori. Second, in order for the algorithm to operate properly, a very good initiation must be performed. Without a very close initiation, the PMHT usually fails to "lock on" to the target correctly. To address both of these issues, a hybrid approach is proposed. This hybrid approach will use a Multi-Hypothesis Tracking (MHT) algorithm to initiate new tracks and to continue tracking them until a track is stable. Then it will hand these tracks off to the PMHT to maintain. The MHT is very good at initiating new tracks, and the PMHT is best at maintaining multiple tracks because the algorithm's complexity with tracking additional targets grows linearly as opposed to exponentially'.