A shortcoming of multichannel sound reproduction standards, such as stereo or 5.1 surround, is their incompatibility with multiple off-axis listening positions. Accurate reproduction of virtual sound sources can only be experienced in the sweet spot, which is located equidistant to the loudspeakers. We here present a novel methodology to compensate audio systems such that the channel similarity is optimized in several listening positions simultaneously. To that end we propose a novel MIMO personal audio filter design framework based on feed-forward control. By proper design choices, filters that successfully compensate for multiple off-axis positions and irregularities in the frequency sum responses are obtained. The design choices include allpass filters with appropriate phase shifts as target for each listening position in addition to a weighted similarity requirement. Evaluations based on measurements of two four-channel car audio systems show that the proposed method significantly improves timbral sound reproduction and phantom center reproduction in several listening positions simultaneously.

A new multichannel approach to robust broadband loudspeaker-room equalization is presented. Traditionally, the equalization (or room correction) problem has been treated primarily by single-channel methods, where loudspeaker input signals are prefiltered individually by separate scalar filters. Single-channel methods are generally able to improve the average spectral flatness of the acoustic transfer functions in a listening region, but they cannot reduce the variability of the transfer functions within the region. Most modern audio reproduction systems, however, contain two or more loudspeakers, and in this paper we aim at improving the equalization performance by using all available loudspeakers jointly. To this end we propose a polynomial based MIMO formulation of the equalization problem. The new approach, which is a generalization of an earlier single-channel approach by the authors, is found to reduce the average reproduction error and the transfer function variability over a region in space. Moreover, pre-ringing artifacts are avoided, and the reproduction error below 1000 Hz is significantly reduced with an amount that scales with the number of loudspeakers used.

In this paper, a new multichannel approach to robust loudspeaker-room equalization is presented. Traditionally, the equalization (or room correction) problem has been treated mostly by single-channel methods, with loudspeaker signals being prefiltered individually by separate scalar filters. Single-channel methods can generally improve the average spectral flatness of the acoustic transfer functions in a listening region, but the variability of the transfer functions within the region cannot be affected. Most modern audio reproduction systems, however, contain two or more loudspeakers, and in this paper we aim at improving the equalization performance by using all available loudspeakers jointly. To this end we propose a general MIMO formulation of the problem, which is a multichannel generalization of an earlier single-channel approach by the authors. The new approach is found to reduce the average reproduction error and the spatial variability of the acoustic transfer functions. Moreover, pre-ringing artifacts are avoided, and the reproduction error below 1000 Hz is significantly reduced with an amount that scales with the number of loudspeakers used.