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Pattern Synthesis Design of Linear Array Antenna with Unequal Spacing Based on Improved Dandelion Optimization

Jianhui Li¹, Yan Liu¹, Wanru Zhao¹

¹School of Physics and Electronic Information, Yunnan Normal University, Kunming 650500, China.

Sensors (Basel, Switzerland)

|February 13, 2025

Summary

A new chaos exchange nonlinear dandelion optimization (CENDO) algorithm improves antenna array patterns by reducing sidelobe levels and creating deep nulls. This enhanced method outperforms existing algorithms in complex electromagnetic environments.

Keywords:

CENDO algorithm logistic–tent chaotic mapping nonlinear control factor synthesis of unequally spaced linear arrays

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Area of Science:

Electromagnetism
Antenna Theory
Optimization Algorithms

Background:

Complex electromagnetic environments necessitate advanced radar systems.
Array antennas are crucial for enhancing radar capabilities against interference and detection.
Existing optimization algorithms struggle with precision and convergence for antenna pattern optimization.

Purpose of the Study:

To introduce the Chaos Exchange Nonlinear Dandelion Optimization (CENDO) algorithm for optimizing non-equidistant antenna array patterns.
To enhance antenna performance by minimizing sidelobe levels (SLL) and achieving deep nulls.
To evaluate the CENDO algorithm's effectiveness against other leading optimization techniques.

Main Methods:

Development of the CENDO algorithm, an improved version of the Dandelion Optimization (DO) algorithm.
Simulation of five experimental examples to test CENDO's performance in optimizing non-equidistant antenna arrays.
Comparative analysis of CENDO against algorithms like DO, PSO, WOA, GOA, SSA, and others.

Main Results:

CENDO achieved the lowest SLL in three simulation examples optimizing non-equidistant arrays.
CENDO demonstrated superior performance in simultaneously reducing SLL and achieving deep nulls in two additional examples.
The algorithm consistently outperformed all compared methods across five experimental simulations.

Conclusions:

The CENDO algorithm offers superior optimization capabilities for non-equidistant antenna array patterns.
CENDO effectively reduces sidelobe levels and deepens nulls, crucial for radar system performance.
This algorithm presents a strong candidate for solving complex electromagnetic problems.