Estimation and Tracking of a Ballistic Target Using Sequential Importance Sampling Method

Abstract

This paper deals with an efficient tracking of a ballistic target by using certain measurements from radar. An efficient non-linear model for the target along with observed error is developed. Since different targets need different models, a specific target with known properties is chosen. Here the target chosen is 9000 mm air launched ballistic missile. This generally weigh more than 5000 kg and its velocity is 2000 m/s. Since these missiles are highly accurate, a 2-D space is chosen as its path. The radar gives the range and the angle of elevation of the missile. The input data processed by state approximation is called as state estimation. Particle filter is used for this non-linear model. Here the observed noise, the processed noise and the radar noise are taken into account. The performance of particle filter is tested and verified with the simulation. By using this particle filter, the range and altitude of this ballistic target can be predicted in advance. The main reason of particle filter’s popularity is that it is very flexible and adaptive. In practical, all non-linear systems has accurate filters.