Synthesizing Algorithms for Tracking Maneuvering Targets using Multi-Revolution Doppler Radar

This paper presents the synthesis and simulation of algorithms for tracking maneuvering targets using multi-revolution Doppler radar, based on the principles of optimal control and optimal filtering in state space. The proposed system consists of two main components: an optimal control block that generates control signals minimizing tracking errors under strong target maneuvers, and an optimal filtering block that accurately estimates target motion parameters such as velocity, acceleration, jerk, and higher-orderderivatives. Simulations were performed for a target approaching with gradually increasing acceleration and high maneuvering frequency. The results demonstrate that the synthesized algorithm achieves high estimation accuracy, fast convergence, strong noise suppression, and stable operation under measurement noise or temporary signal loss. The root mean square error (RMSE) and estimation error plots confirm the high reliability and robustness of the proposed approach.