Automated Interceptor Guidance Based on Multiple Object Tracking

In this contribution automated interception of multiple targets based on object tracking is considered. An unknown amount of maneuvering targets is tracked using the multiple model Gaussian mixture probability hypothesis density filter. The approach utilizes converted measurements so that applicability to nonlinear measurement models is achieved. The tracks are initialized automatically based on the two point differencing method. A track and target management scheme is proposed to detect new targets, and to calculate engagement related data required for the guidance. The proposed method is tested on a 100 km
²
planar surveillance region, where radar-like measurements from unknown targets are simulated. The results show that the proposed approach is capable to manage interception of multiple targets in parallel.