Maneuver detection and tracking with a nonlinear target model

Two approaches to tracking a maneuverable target are presented. The tracking filter comprises two main parts: acceleration estimation and maneuver detection. The acceleration estimator is implemented first by assuming piecewise constant acceleration levels. Maneuver detection is performed to justify the validity of the assumption, i.e. if the acceleration has remained constant. If a maneuver is declared, the filter is reinitialized and a new level of constant acceleration is identified. The second approach is based on a nonlinear state model which gives better tracking for planar maneuvers and non constant accelerations.