Improving beampatterns of two-dimensional random arrays using convex optimization |
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Authors: | Gerstoft Peter Hodgkiss William S |
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Institution: | Marine Physical Laboratory, Scripps Institution of Oceanography, La Jolla, CA 92093-0238, USA. gerstoft@ucsd.edu |
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Abstract: | Sensors are becoming ubiquitous and can be combined in arrays for source localization purposes. If classical conventional beamforming is used, then random arrays have poor beampatterns. By pre-computing sensor weights, these beampatterns can be improved significantly. The problem is formulated in the frequency domain as a desired look direction, a frequency-independent transition region, and the power minimized in a rejection-region. Using this formulation, the frequency-dependent sensor weights can be obtained using convex optimization. Since the weights are data independent they can be pre-computed, the beamforming has similar computational complexity as conventional beamforming. The approach is demonstrated for real 2D arrays. |
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