  The deconvolutional DAMAS algorithm can effectively eliminate the
misconceptions in the usually-used beamforming localization algorithm, allowing
for more accurate calculation of the source location as well as the intensity.
When solving a linear system of equations, the DAMAS algorithm takes into
account the mutual influence of different locations, reducing or even
eliminating sidelobes and producing more accurate results.
  This work first introduces the principles of the DAMAS algorithm. Then it
applies both the beamforming algorithm and the DAMAS algorithm to simulate the
localization of a single-frequency source from a 1.5 MW wind turbine, a complex
line source with the text "UCAS" and a line source downstream of an airfoil
trailing edge. Finally, the work presents experimental localization results of
the source of a 1.5 MW wind turbine using both the beamforming algorithm and
the DAMAS algorithm.

Sound;Audio and Speech Processing