Target tracking and identification using an extended-Kalman-filter-based associative memory

The joint problem of tracking and identification of a target from a airplane is considered. A new powerful combined technique using the extended Kalman filter and an associative memory is used for solving the problem. During tracking of the target it can be identified as one of a finite set of targets, using its feature pattern. Targets can also be identified when only a partial feature vector is available. These techniques are demonstrated through an example, and future research studies are discussed