On the detection of target trajectories in a multi target environment

The tracking and ultimate identification of closely spaced objects is an area of interest to many surveillance systems. Much effort in recent years has been concentrated on the more "front-end" problem of optimizing the initial detection. However, the sorting and processing of crossing tracks and parallel tracks is a problem regardless of signal to noise ratio. In this paper, the application of a pattern recognition approach is investigated. A simulated track scenario is developed and the approach evaluated using the scenario. Examples of performance and results of the simulation study are given.