Modeling of Three-Dimensional Radar Tracking System and Its Estimation using Extended Kalman Filter

摘要

Nowadays, the three-dimensional radar tracking has a rapid development. Tracking filter designs commonly rely on a linear system, while the nonlinear systems mostly occur in everyday life. The development of this filter 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 Filter 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%.