DOA Estimation for Incoherent Signals

In this master's thesis, the author presents a source code implementation for DOA estimation of incoherent signals. This implementation can be applied to various systems including radar systems and acoustic positioning systems. The algorithm processes array-received signals using techniques like Multiple Signal Classification (MUSIC) or Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT), which effectively separate and estimate directions of arrival for uncorrelated signal sources. Through this technology, we can achieve more accurate measurements of signal arrival angles, thereby significantly enhancing signal processing and target localization capabilities. The implementation typically involves covariance matrix computation, eigenvalue decomposition, and spectral peak searching to identify DOA parameters. This technology finds applications not only in military and security domains but also in civilian fields. For instance, it can be integrated into autonomous vehicle perception systems for improved environmental awareness, or deployed in audio conferencing systems to enhance voice signal quality and clarity through spatial filtering and beamforming techniques.