Direction of Arrival (DOA) Estimation: MUSIC and CAPON Algorithms Using Sparse Arrays.

Estimating the direction of arrival (DOA) is crucial for signal localization in various applications including wireless communications, mobile communications, radar, sonar, and smart antenna technology. This study investigates the performance of the MUSIC (Multiple Signal Classification) and CAPON algorithms for DOA estimation utilizing different array geometries. The incorporation of sparse arrays aims to enhance DOA estimation performance in terms of robustness (addressing mutual coupling effects) and degrees of freedom (resolving sources as effectively as possible with the same number of array elements). Through simulations, we compare the DOA estimation performance of various arrays, such as Uniform Linear Array (ULA), Coprime, Cascaded, and Nested arrays. Additionally, we demonstrate that the choice of array geometry can impact the performance of DOA algorithms. The results present pseudo spectra for DOA estimation methods across all considered array configurations. This study endeavors to identify the algorithm that delivers superior accuracy across different array configurations, which holds significant implications for practical applications requiring precise DOA estimation. [ABSTRACT FROM AUTHOR]