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978-3-8439-2669-0, Reihe Ingenieurwissenschaften
Some Contributions to Adaptive Filtering for Acoustic Multiple-Input/Multiple-Output Systems in the Wave Domain
304 Seiten, Dissertation Universität Erlangen-Nürnberg (2016), Softcover, A5
Recently emerging techniques like wavefield synthesis (WFS) or Higher-Order Ambisonics (HOA) allow for high-quality spatial audio reproduction, which makes them candidates for the audio reproduction in future telepresence systems or interactive gaming environments with acoustic human-machine interfaces. In such scenarios, acoustic echo cancellation (AEC) will generally be necessary to remove the loudspeaker echoes in the recorded microphone signals before further processing. Moreover, the reproduction quality of WFS or HOA can be improved by adaptive pre-equalization of the loudspeaker signals, as facilitated by listening room equalization (LRE). However, AEC and LRE require adaptive filters, where the large number of reproduction channels of WFS and HOA imply major computational and algorithmic challenges for the implementation of adaptive filters. A technique called wave-domain adaptive filtering (WDAF) promises to master these challenges. However, known literature is still far away from providing sufficient insight to allow for a successful implementation of real-world systems.
This thesis is concerned with the further development of WDAF-based generic signal processing algorithms and acoustic models aiming at real-time, real-world implementations of AEC and LRE. For both, AEC and LRE, it is necessary to identify an loudspeaker-enclosure-microphone system (LEMS), while the computational demands of this task render a real-time implementation unrealistic, if a large number of reproduction channels should be considered without approximative models.
The originally proposed approximative wave-domain LEMS model is generalized such that the number of degrees of freedom can be chosen to provide the maximum model accuracy given the applicable computational restrictions. Typical reproduction signals will often not allow to find a unique solution to the system identification problem for multichannel reproduction. A novel, rigorous and in-depth analysis of this so-called nonuniqueness problem is conducted in this thesis. Furthermore, a wave-domain technique to improve the system identification when nonuniqueness occurs is presented. This technique does not influence the reproduced signals, as it would be the case for other known state-of-the-art solutions. For an implementation of adaptive filters in the wave domain, modified versions of well-known adaptation algorithms are derived, considering approximative models and improving system identification.