Development and evaluation of a filter for tracking highly maneuverable targets

In modern systems for air surveillance, it is important to have a high quality situation assessment. SAAB has a system for air surveillance, and in this thesis possible improvements of the tracking performance of this system are explored. The focus has been on improving the tracking of highly maneuverable targets observed with low sampling rate. To evaluate improvements of the tracking performance, a component that is similar to the one used in SAAB’s present tracker was implemented in an Interacting Multiple Model (IMM) structure. The use of an Auxiliary Particle Filter for improving the tracking performance is explored, and a way to fit a particle filter into SAAB’s existing IMM framework is proposed. The different filters were implemented in Matlab, and evaluation was done by the means of Monte Carlo simulations. The results from Monte Carlo simulations show significant improvement when tracking in two dimensions. However, the results in three dimensions do not display any substantial overall improvement when using the particle filter compared to using SAAB’s present filter. It is therefore not worthwhile to switch the filter used in SAAB’s present tracker for a particle filter, at least not under the high SNR circumstances presented in this thesis. However, further studies within this area are recommended before any final decisions are made.