Evaluation of automatic track formation with cascaded logic

Tracking of a target in clutter involves the separation of false returns from real ones, which is to be carried out automatically. Logical processes will be applied for the automatic track formation in order to maximize the track, detection probability while keeping a very low level of false tracks. One of the simple loqic processes is the Cascaded Logic of N/(N+K) when a track is declared if there are found at least N returns out of consequent (N+K) measurements. The track detection probability is calculated by means of a recursive equation for the probability mass function. The gates are assumed to let a high return probability and are growing in size when a return is missing. The false track detection probability is also calculated for this model. The evaluation is based on a Markov chain technique.