V2I12P16

Accuracy Improvement of Target Angle Tracking in Long-Range SAM Control Radars via Optimized Filtering

Dang Van Thiet^1*

Abstract

Accurate target angle tracking is essential for the guidance and fire-control performance of long-range surface-to-air missile (SAM) systems. However, measurement noise, nonlinear target motion, and low signal- to-noise ratio (SNR) significantly degrade the angular accuracy of conventional tracking loops. This paper proposes an optimized Kalman filtering approach to improve the estimation accuracy of azimuth and elevation angles in SAM control radars. A complete state-space model of the antenna servo dynamics and radar measurement process is developed, enabling the application of both standard and enhanced Kalman-based filtering strategies. The filtering parameters are optimized to achieve minimum estimation variance under realistic noise and maneuvering conditions. Simulation results demonstrate that the proposed optimized Kalman filtering algorithm reduces angular root-mean-square error (RMSE) by 40–70% compared with classical filtering methods. The improved performance enhances the stability, robustness, and tracking precision of the angle-tracking loop in long-range SAM engagements, providing a practical solution for next- generation missile control radars.

Keywords:

Kalman filter, missile parameter estimation, surface-to-air missile, angle-tracking loop