  We have developed an efficient algorithm for the maximum likelihood joint
tracking and association problem in a strong clutter for GMTI data. By using an
iterative procedure of the dynamic logic process "from vague-to-crisp," the new
tracker overcomes combinatorial complexity of tracking in highly-cluttered
scenarios and results in a significant improvement in signal-to-clutter ratio.
