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Multi-objective Optimization of Interferometric Array u-v Coverage
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AI
DOI：10.1088/1538-3873/ac0f8b.png)
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Abstract
En 中文
A new principle is introduced to optimize the configuration of an interferometric array, based on the trade-off between the uniform and Gaussian u-v distributions. The multi-objective optimization method, nondominated sorting genetic algorithm II (NSGA-II), is applied to achieve the optimal trade-off. The resulting array having a single configuration can meet the observation requirements of both compact and extended sources. This method has been successfully applied to design a 16-element array as the initial stage of the Daocheng Solar Radio Telescope to illustrate its feasibility. NSGA-II is improved by introducing artificial intervention into the genetic operator to solve the equality constraints. The improved NSGA-II is applied to obtain the Pareto optimal set, and a 16-element array configuration is retrieved with the best u-v trade-off between the snapshot mode and Earth rotation synthesis mode.
Keywords:
Interferometers
Algorithms
Solar radio telescopes
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