Feature space transform for multitarget detection

This approach to multitarget tracking is from the perspective of an unsupervised pattern recognition problem. In the usual formulation the target data are processed to produce feature points, which may be track points. The feature points that correspond to the same track are identified when mapped as a dense region in the parameter space. Parameter space representation of crossing and nearly coincident tracks forms overlapping clusters that are not separable. This factor makes the transform approach in its usual form unworkable. Nevertheless, the transform technique need not be abandoned, for the diameter of the aggregate of tracts is evident in the parameter space. Once the direction and location of the aggregate of tracts is located, the individual tracks within the group can be identified by proven techniques.