Low-Sidelobe Pattern Synthesis for Sparse Conformal Arrays Based on Multiagent Genetic Algorithm

Liu, Ganyu; Zhu, Hai‐Liang; Wang, Kai; Qiu, Yuwei; Mou, Jinchao; Zheng, Pei; Gao, Wei

doi:10.1109/ap-s/usnc-ursi47032.2022.9886198

Cited by 3 publications

(1 citation statement)

References 3 publications

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“…Consequently, numerical-pattern synthesis methods for conformal arrays have been a focal point, with numerous efficient approaches proposed over the last two decades. Various techniques, such as Genetic algorithms [20], particle swarm optimization [21], convex optimization [22,23], and adaptive array theory [24] have been explored for conformal-array sum-pattern synthesis. Simultaneously, iterative least-squares [25], convex optimization [9,26], and modified differential evolution algorithms [27] have been examined for conformal-array difference-pattern synthesis.…”

Section: Introductionmentioning

confidence: 99%

On Difference Pattern Synthesis for Spherical Sensor Arrays

Huang,

Chen,

et al. 2024

Sensors

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An innovative method for synthesizing optimum difference patterns of the spherical sensor array is introduced, along with a sidelobe tapering technique. Firstly, we suggest employing the spherical harmonics of degree ±1 to synthesize the spherical array difference pattern; secondly, we study the mapping relationship between the difference pattern of the spherical sensor array and the difference pattern of the uniformly spaced linear array (ULA) with odd-numbered elements; finally, we enhance the Zolotarev difference pattern, which is a counterpart to the Dolph–Chebyshev sum pattern that traditionally allows synthesis only for ULA with even-numbered elements. Our modification extends its applicability to synthesize difference patterns for ULA with odd-numbered elements. Leveraging the optimal difference pattern, a generalized Bayliss difference pattern synthesis method designed for the ULA with odd-numbered elements is further proposed. To illustrate the effectiveness of our approach, we present several design examples through experimental simulation.

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Section: Introductionmentioning

confidence: 99%

On Difference Pattern Synthesis for Spherical Sensor Arrays

Huang,

Chen,

et al. 2024

Sensors

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Fast Pattern Synthesis of Large-Scale Irregular Conformal Arrays Using Genetic Algorithm

Li,

Xu,

Zhang

et al. 2023

2023 IEEE 11th Asia-Pacific Conference on Antennas and Propagation (APCAP)

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Synthesis of the Large-Scaled 64 × 64 Thinned Array Using the Branch and Bound Technique with Convex Optimization for Satellite Communication

Li,

Wang,

Zhang

2024

Electronics

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This paper presents the synthesis of a 64 × 64 thinned array, using the branch and bound technique with convex optimization and a low sidelobe level for satellite communication. The branch and bound technology decomposes optimization into several subproblems. The convex optimization transforms the optimized variable binary [0, 1] of the thinned array into a continuous variable, i.e., from 0 to 1. Based on the branch and bound technique with convex optimization, the fast and accurate convergence of the synthesis of large-scale thinned array was achieved, and 2400 elements were selected for a full 64 × 64 array with a sidelobe level that satisfies the system requirements. The proposed thinned array with 2400 elements was simulated via full-wave 3D simulation. A prototype of the proposed thinned array was fabricated and measured. The simulated and measured results verified the effectiveness of the branch and bound technique with convex optimization.

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Low-Sidelobe Pattern Synthesis for Sparse Conformal Arrays Based on Multiagent Genetic Algorithm

Cited by 3 publications

References 3 publications

On Difference Pattern Synthesis for Spherical Sensor Arrays

On Difference Pattern Synthesis for Spherical Sensor Arrays

Fast Pattern Synthesis of Large-Scale Irregular Conformal Arrays Using Genetic Algorithm

Synthesis of the Large-Scaled 64 × 64 Thinned Array Using the Branch and Bound Technique with Convex Optimization for Satellite Communication

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