Enhanced K-SVD Based Approach for Multi-Source 3D Localization with a Mobile Receiver

Despite its longstanding importance in wireless communications, multi-source localization remains a significant challenge, particularly in scenarios involving moving receivers. This study focuses on the 3D angle of arrival (AOA) localization problem involving multiple sparse signal sources, utilizing a moving receiver with limited antennas. At first, a simple energy detector algorithm is proposed for noise removal in sparse signals. Next, rough angle estimates are obtained by two-dimensional multiple signal classification (2D-MUSIC) and then, a new algorithm based on K-SVD is proposed for precise 2D AOA estimation using a novel sparse recovery method. Finally, a new multi-source 3D-localization algorithm is introduced to estimate the positions of sources using the estimated AOAs. Extensive simulations validate the framework's efficacy, especially in challenging scenarios where the number of sources exceeds the number of antennas.