Sparse Array Optimization Based on Modified Particle Swarm Optimization and Orthogonal Matching Pursuit

Authors

  • Daren Li College of Information and Communication Engineering Harbin Engineering University, Harbin, 150001, China
  • Qiang Guo College of Information and Communication Engineering Harbin Engineering University, Harbin, 150001, China

DOI:

https://doi.org/10.13052/2024.ACES.J.400603

Keywords:

Compressive sensing, orthogonal matching pursuit, particle swarm optimization algorithm, sparse array antenna

Abstract

This paper addresses the low degree of freedom in optimization, primarily attributed to the conventional antenna array optimization methods that solely focus on the optimization of element positions, without considering the influence of element excitations. To address this issue, a sparse array optimization method is proposed based on modified Particle Swarm Optimization (PSO) algorithm and Orthogonal Matching Pursuit (OMP). This method simultaneously optimizes both the element positions and excitations to achieve the desired pattern. Initially, the compressive sensing principle is employed to establish a compressive sensing optimization model for the antenna array. Subsequently, OMP is utilized to simultaneously optimize the element positions and excitations within the antenna array. An improved PSO algorithm is then applied to iteratively update the obtained parameters, thereby further enhancing the peak sidelobe level. Experimental results demonstrate that the proposed algorithm can achieve satisfactory optimization performance.

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Author Biographies

Daren Li, College of Information and Communication Engineering Harbin Engineering University, Harbin, 150001, China

Daren Li was born in Harbin, Heilongjiang Province, China, in 1990. He received the M.S. degree in shipbuilding and ocean engineering from the College of Shipbuilding Engineering, Harbin Engineering University, Harbin, China, where he is currently working toward the Ph.D. degree in information and communication engineering with Harbin Engineering University of Information and Communication Engineering. His research interests include antenna array synthesis, radar signal processing and target comprehensive identification.

Qiang Guo, College of Information and Communication Engineering Harbin Engineering University, Harbin, 150001, China

Qiang Guo received the B.S., M.S., and Ph.D. degrees in information and communication engineering from Harbin Engineering University, China, in 1994, 2003, and 2007, respectively. In 2009, he joined the Faculty with the School of Information and Communication Engineering, Harbin Engineering University, where he is currently a Full Professor. His research interests include antenna array synthesis, machine learning, radar signals sorting, and recognition. He is also a Foreign member of the Ukrainian Academy of Engineering, Review Expert of the Science and Technology Commission of the Military Commission, the National Natural Science Foundation of China and Technology Department evaluation expert and the Chinese Institute of Electronics Science and Technology Award evaluation expert.

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Published

2025-06-30

How to Cite

[1]
D. . Li and Q. . Guo, “Sparse Array Optimization Based on Modified Particle Swarm Optimization and Orthogonal Matching Pursuit”, ACES Journal, vol. 40, no. 06, pp. 508–519, Jun. 2025.

Issue

2025: Vol 40 Iss 6

Section

General Submission

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