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A Hybrid Approach for the Synthesis of Planar Thinned Arrays with Sidelobes Reduction

By combining convex programming (CP) and genetic algorithms (GA), a hybrid method for the synthesis of excitations and locations of planar thinned arrays in order to minimize the side lobe level (SLL) is proposed and discussed in this paper. The approach takes definite advantage from the convexity of the problem with respect to excitation variables, and exploits a GA procedure as far as location variables are concerned. Through a suitable nesting of two optimization procedures, the overall problem can be formulated as a global optimization problem. Moreover, the method is very easy to implement, and it can reach the lowest SLL under the constraint of main lobe and limited number of array elements. Numerical results are conducted to validate the flexibility and effectiveness of the proposed method.