A SIMULATION ANALYSIS OF ALGORITHM BASED ON GLOBAL MSE OPTIMIZATION FOR TARGET TRACKING

Abstract

This paper presents a new approach for reducing the response time in multiple target tracking DAIRKF algorithm .This method is based on to find out global optimality of mean square error (MSE) for multi target tracking. This is of utmost importance for highperformance real-time applications. In this paper we discuss designing of Multi Target Tracking (MTT) algorithm which is based on Kalman filter and to develop an algorithm for multi target tracking such that it will reduce Mean Square Error (MSE) globally. The DAIRKF algorithm is simple in computation while PDA, JPDA algorithms provide exponential terms which increases computational complexity. The idea of this paper is to integrate all targets and measurements . and applied random coefficient matrices Kalman filtering to this integrated dynamic with global MSE optimization algorithm . The VHDL simulation results confirm the validity of this concept. The simulated result shows that the proposed algorithm is better and faster than all previous algorithms (PDA, JPDA, and DAIRKF)