Gain-Focusing Performance Evaluation of Nonlinear Frequency Diverse Arrays

Authors

  • Xin Wang College of Information and Communication Engineering Harbin Engineering University, Harbin, 150001, China
  • Tao Jiang College of Information and Communication Engineering Harbin Engineering University, Harbin, 150001, China
  • Chengkai He College of Information and Communication Engineering Harbin Engineering University, Harbin, 150001, China
  • Gengzuo Liu College of Nuclear Science and Technology Harbin Engineering University, Harbin, 150001, China

DOI:

https://doi.org/10.13052/2026.ACES.J.410408

Keywords:

Gain-focusing area, Nonlinear Frequency Diverse Array, single-point focusing, Two-point Focusing

Abstract

Nonlinear frequency diverse arrays have attracted increasing attention because of their unique point-like focusing characteristics in the joint angle-range domain. However, the quantitative relationship between the focusing pattern and key design parameters, as well as systematic performance evaluation tools, have not been fully established. In this paper, we propose the gain-focusing area as a quantitative metric for assessing the focusing efficiency of nonlinear frequency diverse arrays (NFDA). Unlike conventional one-dimensional beamwidth measures, the gain-focusing area captures the joint angle-range behavior of the array and provides a basis for performance evaluation and design optimization. Using this metric, we systematically study single- and dual-region focusing, and quantify the influence of focusing location (angle, range) and array design parameters (number of elements, frequency-offset coefficient) on the gain-focusing performance. Numerical simulations demonstrate that the proposed gain-focusing-area based evaluation method provides a more reliable performance metric; compared with existing approaches, it nearly doubles the valid angular range while maintaining accurate characterization of the focusing behavior. This enables NFDA spatial focusing capability and parameter sensitivity to be robustly quantified over a wider field of view, offering a more dependable tool for shaping the electromagnetic environment in and around the target region.

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Author Biographies

Xin Wang, College of Information and Communication Engineering Harbin Engineering University, Harbin, 150001, China

Xin Wang was born in 1998. She obtained the B.S. degree from Northeast Electric Power University, Jilin, China, in 2020. She is currently pursuing the Ph.D. degree in information and communication engineering at Harbin Engineering University. Her main research interests include array signal processing.

Tao Jiang, College of Information and Communication Engineering Harbin Engineering University, Harbin, 150001, China

Tao Jiang (Member, IEEE) received the Ph.D. degree from Harbin Engineering University, Harbin, China, in 2002. Since 1994, he has been a Faculty Member of the College of Information and Communication, Harbin Engineering University, where he is currently a Professor. He was a Postdoctoral Researcher with the Research Institute of Telecommunication, Harbin Institute of Technology, Harbin, from 2002 to 2003, and a Visiting Scholar with the Radar Signal Processing Laboratory, the National University of Singapore, from 2003 to 2004. His current research interests include radio wave propagation, electromagnetic modeling and prediction, and electromagnetic environment.

Chengkai He, College of Information and Communication Engineering Harbin Engineering University, Harbin, 150001, China

Chengkai He was born in 2000. He obtained the B.S. degree from Harbin Engineering University, Harbin, China, in 2022. He is currently pursuing a master’s degree in Information and Communication Engineering at Harbin Engineering University, with a primary research focus on antennas.

Gengzuo Liu, College of Nuclear Science and Technology Harbin Engineering University, Harbin, 150001, China

Gengzuo Liu is a second-year Ph.D. student in Nuclear Science and Technology at Harbin Engineering University, China. His research spans radiation detection and protection, nuclear medical physics (FLASH-RT, BNCT), and accelerator beam/beamline design, employing machine learning and multiobjective optimization for fast gamma-ray buildup factor prediction and space-reactor design.

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Published

2026-04-30

How to Cite

[1]
X. . Wang, T. . Jiang, C. . He, and G. . Liu, “Gain-Focusing Performance Evaluation of Nonlinear Frequency Diverse Arrays”, ACES Journal, vol. 41, no. 04, pp. 361–366, Apr. 2026.

Issue

2026: Vol 41 Iss 4

Section

General Submission

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