Microphone Array Signal Processing (Springer Topics in Signal Processing, 1)
In the past few years we have written and edited several books in the area of acousticandspeechsignalprocessing. Thereasonbehindthisendeavoristhat there were almost no books available in the literature when we ?rst started while there was (and still is) a real need to publish manuscripts summarizing the most useful ideas, concepts, results, and state-of-the-art algorithms in this important area of research. According to all the feedback we have received so far, we can say that we were right in doing this. Recently, several other researchers have followed us in this journey and have published interesting books with their own visions and perspectives. The idea of writing a book on Microphone Array Signal Processing comes from discussions we have had with many colleagues and friends. As a c- sequence of these discussions, we came up with the conclusion that, again, there is an urgent need for a monograph that carefully explains the theory and implementation of microphone arrays. While there are many manuscripts on antenna arrays from a narrowband perspective (narrowband signals and narrowband processing), the literature is quite scarce when it comes to s- sor arrays explained from a truly broadband perspective. Many algorithms for speech applications were simply borrowed from narrowband antenna - rays. However, a direct application of narrowband ideas to broadband speech processing may not be necessarily appropriate and can lead to many m- understandings.
Why Read This Book
You will get a focused, research-to-practice treatment of microphone array techniques that links classical beamforming and spectral methods with modern adaptive, statistical, and multichannel audio algorithms. The book emphasizes practical algorithmic detail and evaluation, so you can move from theory to implementable DSP solutions for speech, audio, and acoustic sensing applications.
Who Will Benefit
Engineers or graduate students with DSP and linear algebra background who are designing or researching multichannel audio systems, hands-free telephony, hearing devices, or acoustic sensing/robotics applications.
Level: Advanced — Prerequisites: Solid fundamentals in digital signal processing (FFT, filtering, STFT), linear algebra, probability/statistics, and basic acoustics; familiarity with MATLAB or similar numerical tools.
Key Takeaways
- Design and implement classical and modern beamformers (delay-and-sum, MVDR/LCMV, superdirective) for microphone arrays
- Estimate source direction and spatial structure using subspace and parametric methods (MUSIC, ESPRIT) and time-delay techniques (GCC-PHAT)
- Apply multichannel spectral processing and adaptive filtering (multichannel Wiener, LMS/RLS variants) for noise suppression and echo control
- Analyze and mitigate reverberation and array mismatch through dereverberation, calibration, and robustness strategies
- Translate theory into practice using frequency-domain implementations, FFT-based processing, and real-world performance evaluation
Topics Covered
- Introduction and historical overview of microphone arrays
- Acoustical fundamentals, array geometry, and spatial sampling
- Array signal models and statistical representations
- Classical beamforming: delay-and-sum and frequency-domain implementations
- Optimal and adaptive beamforming: MVDR, LCMV, and adaptive algorithms
- Superdirective beamformers and robustness to array mismatch
- Time-delay estimation and cross-correlation methods (GCC-PHAT)
- Direction-of-arrival estimation: MUSIC, ESPRIT and subspace techniques
- Multichannel spectral processing: STFT, FFT-based filtering, and multichannel Wiener filters
- Blind and semi-blind source separation for audio (ICA, time-frequency masking)
- Dereverberation, echo cancellation and reverberant environment modeling
- Practical considerations: calibration, microphone mismatch, hardware implementation and case studies
- Appendices: MATLAB examples, simulation tools and datasets
Languages, Platforms & Tools
How It Compares
Covers similar ground to Brandstein & Ward's 'Microphone Arrays' but is more algorithm-focused with deeper treatment of adaptive/statistical methods and practical frequency-domain implementations.
