Tracking of maneuvering non-ellipsoidal extended target with varying number of sub-objects

A target that generates multiple measurements at each time step is called the extended target and an ellipse can be used to approximate its extension. When the spatial distributions of measurements can reflect its true shape, in this situation the extended target is called a non-ellipsoidal extended target and its complicated extended state cannot be accurately approximated by single ellipse. In view of this, the non-ellipsoidal extended target tracking (NETT) filter was proposed, which uses multiple ellipses (called sub-objects) to approximate the extended state. However, the existing NETT filters are limited to the framework that the number of sub-objects remains still, which does not match the actual tracking situations. When the attitude of the target changes, the view from the sensor on the target may change, then the shape of the non-ellipsoidal extended target varies as well as the reasonable number of sub-objects needed for approximation. To solve this problem, we propose a varying number of sub-objects for non-ellipsoidal extended target tracking gamma Gaussian inverse Wishart (VN-NETT-GGIW) filter. The proposed filter estimates the kinematic, extension and measurement-rate states of each sub-object as well as the number of sub-objects. The simulation results show that the proposed filter can be used for the target changing attitude situation and is more close to the practice application.