Efficient Binaural Display using MIMO State-Space Systems

Binaural displays for immersive listening must model reverberant acoustic environments, multiple sound sources, and compensate for head motion. Many displays accomplish this by convolving collections of spatially distributed sources with head-related transfer functions (HRTFs). In the absence of reflections, the computational load scales linearly with the number of sources; however, when reflections are present, the load scales exponentially such that the binaural display reaches the limit of available processing power for even relatively sparse acoustic scenes. We propose a method that significantly eases this exponential growth by formulating the HRTF filter array as a MIMO state-space system. Two MIMO architectures are explored; the relative merits of each are found to depend on the specific application. Hankel-optimal methods are found to be a good choice for model reduction, and yield displays with superior approximation quality relative to conventional FIR filter arrays of equal computational complexity.