Background. In wireless communication, Doppler shift—caused by relative motion between the transmitter and receiver—poses a significant challenge to Direction of Arrival (DOA) estimation. This issue is particularly critical in Directional Modulation (DM) systems, which enhance physical layer security by controlling the directionality of transmitted signals. However, existing DOA estimation methods struggle in dynamic environments where Doppler-induced distortions impact accuracy, leaving a gap in secure beamforming techniques.

Objectives. This thesis proposes a novel joint Doppler-DOA estimation framework to address these challenges. The study focuses on analyzing how Doppler shift affects traditional DOA estimation methods, designing an improved algorithm for joint estimation, and evaluating its performance in varying conditions.

Methods. The proposed approach is tested using MATLAB-based simulations, incorporating a Uniform Linear Array (ULA) antenna system and modeling real-world wireless scenarios. Key performance metrics are used to assess its effectiveness, including estimation accuracy, bit error rate (BER) and signal-to-interference-plus-noise ratio (SINR).

Results. The findings suggest that integrating Doppler shift compensation into DOA estimation significantly improves accuracy and enhances the security of DM systems. By simulation results shows that Kalman filtering integration helps lower BER, reduce DOA estimation errors, and increase secrecy capacity across mobility scenarios. This ensures proposed model provides reliable and secure communication even in high mobility.

Conclusions. The results validate the proposed system featuring MIMO processing, Kalman-based Doppler DOA estimation, and artificial noise injection (AN), which offers an improvement over traditional models. Mainly strengthens PLS by signal integration and directionality in mobility scenarios. This research contributes to developing robust and secure wireless networks, particularly for high-mobility applications such as autonomous vehicles, IoT, and next-generation communication systems.