ΠΠ·Π΄Π°ΡΠ΅Π»ΡΡΡΠ²ΠΎ Springer, 2007, -267 pp.
Many applications of acoustic signal processing, such as teleconferencing and surveillance systems, require an estimate of several parameters present in the observed acoustic scene. The most important parameters are the location of the acoustic sources as well as the number of currently active sources. These parameters have been traditionally estimated by means of classical array signal processing using microphone arrays. The term classical is used here to classify algorithms that are derived from the microphone signals directly. In contrast, the algorithms presented in this book are not solely based on classical array signal processing but also on the principles of wave propagation and wave scattering offered by the science of classical acoustics. Novel so-called modal array signal processing algorithms can now be derived from the fundamental solutions of the acoustic wave equation.
Algorithms for parameter estimation solely based on the paradigm of classical array signal processing often suffer from the problem that they rely on a narrowband assumption underlying the signal model, which limit their usability when broadband signals, such as speech, are present in the wavefield under observation. It will be shown that by additionally considering the paradigm of classical acoustics algorithms can be derived that are inherently broadband hence allowing for ubiquitous application.
Moreover, it will be shown that parameter estimation, methods, has the potential to umunbiguously detect and localize multiple simultaneously active wideband sources in the array's full field-of-view.
In order to take advantage of the paradigms that can be found in the field of acoustics, special array geometries are considered here, i.e. circular and spherical geometries for the analysis of wave propagation in two and three spatial dimensions, respectively.
A rigorous derivation of modal array signal processing algorithms for parameter estimation as well as performance evaluations by mean of simulations and measurements using an actual real-time capable implementation are discussed.
Introduction.
Acoustic Wavefields.
Wayfield Decomposition.
Acoustic Scene Analysis Using Classical Array Signal Processing.
Acoustic Scene Analysis Using Modal Array Signal Processing.
A Practical Acoustic Scene Analysis System.
Summary and Conclusions.
A Signal Transforms.
B Special Functions.
C Microphone Arrays and Nearfield/Farfield Sources.
D Eigenbeam-CRLB for a Single Source.
E Frequency-Independence of EB-ESPRIT for a Single Source.
F A Practical Acoustic Scene Analysis System β Further Results.