Optimal array configuration search using genetic algorithm

Details Optimal array configuration search using genetic algorithm Optimal array configuration search using genetic algorithm

Dec 2001

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2001spie.4472..518f&link_type=abstract

Proc. SPIE Vol. 4472, p. 518-527, Applications of Digital Image Processing XXIV, Andrew G. Tescher; Ed.

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Radio astronomy interferometric arrays traditionally use Earth rotation aperture image synthesis. Existing radio telescopes consist of dozens antennas separated at hundreds and thousands wavelengths, and these arrays are very sparse comparing to the common radar & communications phased arrays. New projects of superlarge radio telescopes, Square Kilometer Array (SKA), Low Frequency Array (LOFAR), Atacama Large Millimeter Array (ALMA) presume both Earth rotation and snapshot imaging. Optimizing an array configuration is an important stage of the array design. Due to the sparseness of the radio interferometers, the following cost functions might be chosen during optimization process: sidelobe minimization, or, in more specific way, the maximum sidelobe amplitude or the baseline histogram. Genetic algorithm is proposed in this paper for solving the optimization problem. It provides the global maximum of a cost function in a multimodal task and admits easy implementation of different constrains: desirable angular resolution (maximal antenna spacing), sensitivity to extended image features (minimal spacing), topography limitations, etc. Several examples of array configuration optimization using genetic algorithms are given in the paper.

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