Advanced Multitarget Tracking Algorithm using Kalman Filter

Advanced multitarget tracking algorithm using kalman filter is presented in this paper. Multitarget tracking is widely used in surveillance of objects in dense clusters in real time applications such as radars, military operations, and space technology. Kalman filter is a recursive filter which is used for such real time applications. Several various algorithms has been developed and implemented for target tracking. But there was some limitations regarding cluster density, estimation time and accuracy. A new improved DAIRKF algorithm is presented in this paper, whose performance is far more appreciable in complex cluster density of objects also. The main goal of implementing this algorithm is to reduce error which occurs during estimation of target using kalman filter and global mean error optimization so that original target can be traced with more accuracy.