Abstract
This paper addresses the problem of designing shaped beam patterns with arbitrary arrays subject to constraints. The constraints could include the sidelobe level suppression in specified angular intervals, the mainlobe halfpower beamwidth, and the predefined number of elements. In this paper, we propose a new Differential Evolution algorithm, which combines Composite DE with an eigenvector-based crossover operator (CODE-EIG). This operator utilizes eigenvectors of covariance matrix of individual solutions, which makes the crossover rotationally invariant. We apply this novel design method to shaped beam pattern synthesis for linear and conformal arrays. We compare this algorithm with other popular algorithms and DE variants. The results show CODE-EIG outperforms the other DE algorithms in terms of statistical results and convergence speed.
Highlights
Array synthesis is a classic and challenging optimization problem, which has been extensively studied using several analytical or stochastic methods [1,2,3,4]
One of the Differential Evolution (DE) advantages is that very few control parameters have to be adjusted in each algorithm run
We have presented a novel design approach for shaped beam pattern synthesis with multiple constraints based on Differential Evolution
Summary
Array synthesis is a classic and challenging optimization problem, which has been extensively studied using several analytical or stochastic methods [1,2,3,4]. Composite DE (CODE) [22] is an adaptive DE variant, which combines three different trial vector generation strategies with three preset control parameter settings. In CODE, the crossover operator is not applied for the DE/current-to-rand/1 strategy.
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