Numerical annealing of low-redundancy linear arrays

CS Ruf - IEEE Transactions on Antennas and Propagation, 1993 - ieeexplore.ieee.org
IEEE Transactions on Antennas and Propagation, 1993ieeexplore.ieee.org
An algorithm is developed that estimates the optimal distribution of antenna elements in a
minimum redundancy linear array. These distributions are used in thinned array
interferometric imagers to synthesize effective antenna apertures much larger than the
physical aperture. The optimal selection of antenna locations is extremely time consuming
when large numbers of antennas are involved. This algorithm uses a numerical
implementation of the annealing process to guide a random search for the optimal array …
An algorithm is developed that estimates the optimal distribution of antenna elements in a minimum redundancy linear array. These distributions are used in thinned array interferometric imagers to synthesize effective antenna apertures much larger than the physical aperture. The optimal selection of antenna locations is extremely time consuming when large numbers of antennas are involved. This algorithm uses a numerical implementation of the annealing process to guide a random search for the optimal array configuration. Highly thinned low-redundancy arrays are computed for up to 30 array elements. These arrays are equivalent to the optimal solutions that are known for up to 11 elements. The arrays computed for 12-30 elements have the fewest redundancies reported to date.< >
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