Adding Sparse Recovery to Projective Ray Space Analysis

摘要: Integrating sparse recovery methods into the ray space transform is a new and recent area of investigation for microphone arrays. A previous exploration using single array resulted in method that shows promise. Nevertheless, primary advantage approach derives from its robust ability to integrate information multiple arrays viewpoints. Therefore, this work, we explore integration across two viewpoints provided by separate Because working with domain requires use projective geometry, viewpoint. Numerical simulations demonstrate integrating improves results space. In particular, show an improvement quality acoustic images. Results also indicate utility extent projection depends strongly on distance between source array.