Sparse Array

Sparse arrays are non-uniform antenna configurations designed to achieve super-resolution, enabling the localization of more sources than the number of physical sensors. Current research focuses on developing advanced algorithms, including subspace-based methods like MUSIC and generalized coarray MUSIC, and deep learning approaches to improve direction-of-arrival estimation and mitigate issues like sensor calibration errors and coherent sources. These advancements are significant for applications such as radar imaging, wireless communications, and array signal processing, offering improved resolution and robustness in challenging environments.