| Citation: | Zhikun CHEN, Kang DU, Dongliang PENG, Xinting ZHU. Planar Sparse Array Constraint Optimization Based on Hybrid Trigonometric Mutation Differential Evolution Algorithm[J]. Journal of Electronics & Information Technology, 2020, 42(4): 895-901. doi: 10.11999/JEIT190705
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For the problems of sparse planar array optimization with side-lobe concave nulls constraints and premature algorithm, a Hybrid Trigonometric Mutation Differential Evolution (HTMDE) algorithm is proposed based on the idea of parameter adaptation. By introducing side-lobe concave nulls constraints matrix, adaptive penalty function is constructed. Time-varying weight combination mutation strategy and crossover strategy improve the initial global search ability and late convergence ability of the algorithm. The constrained optimization of the planar array with peak side lobe level and side-lobe concave nulls is finally realized. The simulation results show that, compared with the algorithm before the hybrid trigonometric mutation strategy, the algorithm not only optimizes the peak side-lobe level of sparse array, but also designs concave nulls in specified side-lobe area to reduce the influence of active interference.
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