Multi-objective Optimization of Interferometric Array u–v Coverage

Abstract

Abstract 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.