Time Domain Beamforming (TDBF) and Frequency Domain Beamforming (FDBF) are two widely adopted techniques in the realm of acoustic signal processing. Their primary goals include refining source localization, enhancing the quality of recorded audio signals and facilitating the separation of multiple sound sources within a particular environment.
In the table below, the commonalities of and differences between TDBF and FDBF are presented, while the specific advantages of each technique and their corresponding applications areas are highlighted.

 Time Domain Beamforming (TDBF)Frequency Domain Beamforming (FDBF)
CommonalitiesEqual imaging methods, achieve the same results
Frequency-selective analysis, TDBF requires band-pass filtering of the time signal

Both use time correlation between the microphone signals

Both realise spatial filters to enhance or attenuate sounds at mapped locations
CLEAN deconvolution algorithms exist:
AdvantagesFast for short recordings

Efficient processes of long-time signals by pre-calculating the Cross-Spectral Matrix (CSM)

Small data volumes when creating/saving acoustic moviesFast and uncomplicated frequency-dependent analysis
Low computational complexityMultitude of extended algorithms: Power BF, Orthogonal BF…, all based on the CSM
Suitable for processing strongly time-varying/transient signalsHigh localization accuracy even at low sampling rates e. g. 24 kHz
DisadvantagesFrequency analysis requires additional band-pass filtering in advance (multiple-band analysis is more demanding)Suitable for efficient processing of stationary signals
Almost no advanced algorithms applicableSpectral leakage due to Short-Time Fourier Transform (STFT) process may affect FDBF results
Application AreasSound source localization
Engine analysis
Virtual microphoneWind tunnel
Pass-byLeakage detection
Wind turbinesRoom acoustics
Squeak & rattle test 

Further Reading

Visit the website Berlin Beamforming Conference held by GFaI e. V. https://www.bebec.eu.