Modeling of head related transfer functions for immersive audio using a state-space approach

Accurate localization of sound in 3-D space is based on variations in the spectrum of sound sources. These variations arise mainly from reflection and diffraction effects caused by the pinnae and are described through a set of head-related transfer functions (HRTFs) that are unique for each azimuth and elevation angle. A virtual sound source can be rendered in the desired location by filtering with the corresponding HRTF for each ear. Previous work on HRTF modeling has mainly focused on methods that attempt to model each transfer function individually. These methods are generally computationally-complex and cannot be used for real-time spatial rendering of multiple moving sources. We provide an alternative approach, which uses a multiple-input single-output state-space system to create a combined model of the HRTFs for all directions. This method exploits the similarities among the different HRTFs to achieve a significant reduction in the model size with a minimum loss of accuracy.