Modeling of three-dimensional radar tracking system and its estimation using Extended Kalman Filter

Nowadays, the three-dunensional radar tracking has a rapid deveiopment lï'acldiig filter designs commonly rely on a linear system, while the nonlinear systems mostly occur in everyday life. The development of this fUter algorithm can solve the three-dimensional radar tracking problem by using some measurement data. In the case discussed in this paper, the target is measured by radar with distance r, azimuth angle Θ, and the elevation angle φ. Notice that the data is not a linear measurement data. Thus, to address the nonlinearities inherent in the system model and the measurement model, we use the Extended Kalman FUter approach. Variables and parameters are adjusted directly on the three-dimensional radar system. The simulation results show that the proposed formulation is very effective in the calculation of nonlinear measurement with the error belongs to interval from 0.69% to 1.21%.