Real time benefits of fixed lag smoothing for multi-target tracking and interception system

The aim of this paper is to propose a smoothing method within the Kalman filter framework for recursive tracking and interception of multiple point targets moving in the surveillance area. This work builds the real time benefits of fixed lag smoothing to the Kalman filter state trajectory estimates for both tracking and interception task as well. Smoothing based decision to activate the guidance system is evaluated to follow and intercept the moving target in the surveillance area before it reaches it's destination. The interception task for the follower is achieved by calculating the range and azimuth using basic geometrical rules. The performance parameters i.e. root mean square error (RMSE) and hit error (HE) of the Kalman filter estimates are compared with that obtained by smoothed state trajectory estimates.