A method for quickly optimizing element positions of a low-sidelobe circular-aperture symmetric sparse array

CN117787088BActive Publication Date: 2026-11-03SHANGHAI RADIO EQUIP RES INST
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Patent Information

Application Number
CN202311682092.1
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2023-12-08
Publication Date
2026-11-03
Estimated Expiration
2043-12-08

AI Technical Summary

Technical Problem

Existing technologies have limited freedom of element variation when optimizing sparsely distributed circular aperture arrays, resulting in higher sidelobes in the optimized array pattern. Furthermore, the channel spacing of less than 1.5 mm becomes a challenge in high-frequency design.

Method used

By mapping the positions of array elements in a rectangular sparse array to a circular space and using a genetic algorithm to optimize the positions of the array elements, the random distribution of array elements in the circular space is achieved, thereby reducing the sidelobe level.

Benefits of technology

The optimized array element positions neither exceed the constraint region nor completely cover the entire circular surface, reducing the simulation workload and the difficulty of the TR-to-antenna conversion network, and are suitable for large-scale sparse antenna arrays.

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Abstract

The application provides a method for quickly optimizing element position of a low-side-lobe circular-aperture symmetric sparse array, comprising the following steps: H1, establishing an initial population complex matrix B, a rectangular boundary plane submatrix S', and a matrix C; H2, mapping each point in the rectangle to a point in a second pseudo-fan, and each point in the second pseudo-fan corresponds to each element in a two-dimensional matrix S(:,:,i) of a pseudo-fan boundary submatrix S; H3, mapping the submatrix S into a circular boundary symmetric plane sparse array position matrix D; H4, multiplying a two-dimensional matrix D(:,:,i) of the matrix D with [C,C;C,C] to obtain a two-dimensional position matrix D*(:,:,i); H5, calculating a directivity pattern of each two-dimensional position matrix corresponding to a population, establishing a fitness matrix F, recording an optimal population, and optimizing and updating the two-dimensional position matrix based on a genetic algorithm; repeating the step H5 until a set stop updating condition is met; and the two-dimensional position matrix corresponding to the optimal population is an optimal circular boundary symmetric plane sparse array position matrix.
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