Tracking through Occlusions and Track Segmentation Reduction

In a target tracking situation, with clutter measurements and uncertain detections, true tracks often get lost due to temporal occlusions or unfavourable detection sequences, as well as the effects of measurement noise, clutter measurements, or any combination thereof. After a detection delay a new track is then initialized and subsequently confirmed for the same target, and the track becomes segmented. The Markov chain two (MC2) model for target existence propagation includes this temporal loss of detectability and often allows the track to continue through adverse conditions. This paper integrates the MC2 model with the integrated track splitting (ITS) algorithm resulting in a significant reduction of track segmentation.