fbeamform¶

Implements beamformers in the frequency domain.

`SteeringVector`	Basic class for implementing steering vectors with monopole source transfer models.
`BeamformerBase`	Beamforming using the basic delay-and-sum algorithm in the frequency domain.
`BeamformerFunctional`	Functional beamforming algorithm.
`BeamformerCapon`	Beamforming using the Capon (Mininimum Variance) algorithm.
`BeamformerEig`	Beamforming using eigenvalue and eigenvector techniques.
`BeamformerMusic`	Beamforming using the MUSIC algorithm.
`BeamformerClean`	CLEAN deconvolution algorithm.
`BeamformerDamas`	DAMAS deconvolution algorithm.
`BeamformerDamasPlus`	DAMAS deconvolution [3] for solving the system of equations, instead of the original Gauss-Seidel iterations, this class employs the NNLS or linear programming solvers from scipy.optimize or one of several optimization algorithms from the scikit-learn module.
`BeamformerOrth`	Orthogonal deconvolution algorithm.
`BeamformerCleansc`	CLEAN-SC deconvolution algorithm.
`BeamformerCMF`	Covariance Matrix Fitting algorithm.
`BeamformerSODIX`	Source directivity modeling in the cross-spectral matrix (SODIX) algorithm.
`BeamformerGIB`	Beamforming GIB methods with different normalizations.
`BeamformerAdaptiveGrid`	Base class for array methods without predefined grid.
`BeamformerGridlessOrth`	Orthogonal beamforming without predefined grid.
`PointSpreadFunction`	The point spread function.
`L_p`(x)	Calculates the sound pressure level from the squared sound pressure.
`integrate`(data, grid, sector)	Integrates a sound pressure map over a given sector.

Acoular 24.10 documentation