METHODS AND APPARATUS FOR HIGHER ORDER AMBISONICS DECODING BASED ON VECTORS DESCRIBING SPHERICAL HARMONICS

摘要

The encoding and decoding of HOA signals using Singular Value Decomposition includes forming based on sound source direction values and an Ambisonics order corresponding ket vectors (|Y(Ω_s)) of spherical harmonics and an encoder mode matrix (Ξ_O×S). From the audio input signal (|x(Ω_s)) a singular threshold value (σ_s) determined. On the encoder mode matrix a Singular Value Decomposition is carried out in order to get related singular values which are compared with the threshold value, leading to a final encoder mode matrix rank (r_fine). Based on direction values (Ω_l) of loudspeakers and a decoder Ambisonics order (N_l), corresponding ket vectors (|Y(Ω_l)) and a decoder mode matrix (Ψ_O×L) are formed. On the decoder mode matrix a Singular Value Decomposition is carried out, providing a final decoder mode matrix rank (r_find). From the final encoder and decoder mode matrix ranks a final mode matrix rank is determined, and from this final mode matrix rank and the encoder side Singular Value Decomposition an adjoint pseudo inverse (Ξ⁺)^† of the encoder mode matrix (Ξ_O×S) and an Ambisonics ket vector (|a′_s) are calculated. The number of components of the Ambisonics ket vector is reduced according to the final mode matrix rank so as to provide an adapted Ambisonics ket vector (|a′_l). From the adapted Ambisonics ket vector, the output values of the decoder side Singular Value Decomposition and the final mode matrix rank an adjoint decoder mode matrix (Ψ)^† is calculated, resulting in a ket vector (|y(Ω_l)) of output signals for all loudspeakers.