DIRECTION OF ARRIVAL (DOA) ESTIMATION FOR SMART ANTENNAS IN WEATHER IMPACTED ENVIRONMENTS

Direction of arrival estimation (DOA) is critical in antenna design for emphasizing the desired signal and minimizing interference. The scarcity of radio spectrum has fuelled the migration of communication networks to higher frequencies. This has resulted in radio propagation challenges due to the adverse environmental elements otherwise unexperienced at lower frequencies. In rainfallimpacted environments, DOA estimation is greatly affected by signal attenuation and scattering at the higher frequencies. Therefore, new DOA algorithms cognisant of these factors need to be developed and the performance of the existing algorithms quantified. This work investigates the performance of the Conventional Minimum Variance Distortion-less Look (MVDL), Subspace DOA Estimation Methods of Multiple Signal Classification (MUSIC), and the developed estimation algorithm on a weather impacted wireless channel, Advanced-MUSIC (A-MUSIC). The results show performance degradation in a rainfall impacted communication network with the developed algorithm showing better performance degradation.