Low Sidelobe Optimization Design of Conformal Sparse Array Antenna using Active Pattern

Aiming at the optimization problem of the sidelobe level of conformal sparse array antenna, a design method based on weighted random sampling and multi-population genetic algorithm is proposed in this paper. Firstly, under the condition of full array of conformal array antenna, the elements that have little influence on the radiation characteristics of the array is sparsified. Then, beam scanning and sidelobe level optimization are carried out on the sparse conformal array antenna. Due to the conformal and sparse requirements of the array, the radiation characteristics of each array element in the array antenna are different. The Active Element Pattern (AEP) of each array antenna unit is obtained by using ALTAIR FEKO software. In order to improve the optimization accuracy and efficiency, the genetic algorithm and the multi-population cooperative mechanism is used to optimize the array antenna unit. The radiation characteristics of the conformal sparse array antenna calculated by this method are in good agreement with the test results and have strong engineering application value.