Uncorrelated input signals design and identification with low-complexity for simultaneous estimation of head-related transfer functions

In our previous study, we verified that a set of head-related transfer functions (HRTFs) can simultaneously be estimated by treating it as a multi-input single-output (MISO) system. However, this leads to a lack of accuracy if appropriate input signals are not chosen, and high computational cost is required to estimate. To improve the accuracy, a novel input design method is proposed. Moreover, we also propose a system identification method which reduces the space complexity even when the number of measuring directions increases. The effectiveness of the proposed methods was demonstrated through simultaneous estimation experiments of HRTFs.