Fusion Architectures for 3D Target Tracking Using IRST and Radar Measurements

Abstract

Seven different architectures are presented to fuse IRST and radar data to track the target in 3D Cartesian coordinates, with the measurements available in polar coordinates. Performance of these architectures is checked with simulated data. Detailed mathematical expressions are provided which could be useful for algorithm implementation. From this study, it is concluded that CM (Common Measurements) architecture gives state estimates with relatively less uncertainty followed by SVF (State Vector Fusion). IRST gives target states with relatively high uncertainty followed by radar. This shows the necessity of the fusion in tracking system. In all, CM architecture is very simple, easy to implement and can be used in real time.