Performance analysis for blind identification of acoustic channels

Multichannel blind system identification is a prominent part in audio dereverberation. Despite much progress in this field, the performance of existing algorithms is still unsatisfactory and existing theories have failed to properly explain the issue. To assess performance impediments, we introduce, quantify, and illustrate three major sources of errors: namely, estimation, approximation, and referencing errors. For each error, we provide simple expressions that describe the effect of various system parameters and that can serve as a guideline to explain reality and improve performance.