A julia package for Aeroacoustics
Author 1oly
17 Stars
Updated Last
5 Months Ago
Started In
January 2019


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A julia package for Aeroacoustics and acoustic imaging.



This package provide methods for working with microphone array measurements. Utilities for processing beamforming and other acoustic imaging methods are collected in this package, and it is the intention, that a suite of both well-known and state of the art methods is continuously updated.

The current set of methods include conventional frequency domain beamforming (CBF) with source power integration (SPI), and the following advanced methods:

Method Reference
DAMAS Brooks, T. F. et al. (2006). A deconvolution approach for the mapping of acoustic sources (DAMAS) determined from phased microphone arrays. J. Sound Vib. 294(4), 856–879.
CLEAN-SC Sijtsma, P. (2007). CLEAN based on spatial source coherence. Int.J.Aeroacou. 6(4), 357–374.
FISTA - Beck, A., & Teboulle, M. (2009). A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM J. Imag. Sci., 2(1), 183-202.
- Lylloff, O., et al. (2015). Improving the efficiency of deconvolution algorithms for sound source localization. J. Acou. Soc. Am, 138(1), 172-180.

On the roadmap is:

Method Reference
Functional beamforming Dougherty, R.P. (2014). Functional beamforming. 5th Berlin Beamforming Conference, February 19–20 2014, Berlin, Germany, GFaI, e.V., Berlin.
Orthogonal beamforming  Sarradj, E. (2010). A fast signal subspace approach for the determination of absolute levels from phased microphone array measurements. J. Sound Vib. 329(9), 1553–1569.
Spectral Estimation Method (SEM) /
Covariance Matrix Fitting (CMF)
Blacodon, D. et al. (2004). Level estimation of extended acoustic sources using a parametric method. J. Airc. 41, 1360–1369.
Yardibi, T. et al. (2010). A covariance fitting approach for correlated acoustic source mapping. J. Acoust. Soc. Am. 127(5), 2920–2931.
Generalized Inverse Beamforming (GIBF) Suzuki, T. (2011). L1 generalized inverse beamforming algorithm resolving coherent/incoherent, distributed and multipole sources. J. Sound Vib. 330(24), 5835–5851.

Additional methods can also be added by contributors to this repository. The code structure enables an easy and modular addition of new methods.

Denoising of the cross-spectral matrix is another important part of succesful acoustic imaging. Several different methods are on the roadmap to be implemented.

Source integration of acoustic images is another important feature of this package. The output can be produced in narrow-band, 1/3rd or 1/12th octave bands.


First install julia and start julia in a terminal, VS code, Jupyter or another application that can run julia. This package is registered and can be installed with

pkg> add AeroAcoustics

the package manager pkg> can be accessed by typing ].


Contributions are welcome! Issues are tracked on Github issue tracker. If you want to add an new algorithm, you can fork this package and start developing your code and test it.

Related packages

Another noteworthy library for microphone array measurements is Acoular, written in Python. AeroAcoustics.jl draws inspiration from Acoular but focusses only on the processing of measurement data, while Acoular also has functionality for generating simulated data.

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