Abstract
A fast simulated annealing algorithm is developed for an optimal time-domain beamformer. The optimal beamformer has greater resolution than the standard frequency-domain beamformers, which discard information by averaging the data to form a correlation matrix and remove degrees of freedom by collapsing the number of unknown parameters. The optimal ambiguity function uses the data in raw form and depends on all of the unknown source parameters. This approach is practical with simulated annealing. A specialized simulated annealing algorithm is required to search for the source bearings and time series because the parameters are analogous to a mixture of substances with different freezing points. Examples are presented to demonstrate that the optimal beamformer can be enhanced significantly with a priori information and to illustrate the effects of source level and bandwidth, noise level, array size, and number of sources.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
