APAN-Based Direction of Arrival Estimation and Signal in UAV Communication Platforms

Direction of Arrival estimation in UAV (Unmanned Aerial Vehicle) systems is required for navigation, beam estimation and pattern formation, localization and interference suppression. The factors that affect the system accuracy are UAV mobility, multipath propagation, low signal to noise ratio etc. The proposed solution to these problems is the use of Adaptive Phase Antenna Network based Direction of Estimation for UAV communications. The methodology proposed utilizes the combination of signal processing of antenna array, adaptive beam formation, covariance matrix estimation, angle prediction using deep learning. The parameters optimized using the proposed methodology are angular resolution, localization accuracy, reduction in complexity under dynamic environment. The simulation results showcase that the parameters like Root Mean Square Error, detection probability and robustness are improved as compared to ESPRIT and MUSIC algorithm architechture.