Genetic Algorithm for Sparse Optimization of Mills Cross Array Used in Underwater Acoustic Imaging
Teng D, Li Y, Yang H, Wei Z, Li Y (2022)
Publication Type: Journal article
Publication year: 2022
Journal
Book Volume: 10
Article Number: 155
Journal Issue: 2
DOI: 10.3390/jmse10020155
Abstract
Underwater acoustic imaging employs a special form of array which includes numerous transducer elements to achieve beamforming. Although a large-scale array can bring high imaging resolution, it will also cause difficulties in hardware complexity and real-time application. In this paper, in order to reduce the number of array elements, a sparse optimization for Mills cross is pro-posed, considering the elements’ distributions and weights design. The improved genetic algorithm is adopted to generate evolutions for sparse solution. In order to ensure effective convergence and successful evolution, relevant genetic operators are proposed, including appropriate population coding, correct fitness function, reasonable selection strategy and efficient two-point orthogonal crossover, among others. Essentially, a satisfied sparse solution is a result of mutual restraint between array elements’ survivals and their weights. The simulations reveal that our sparse cross array decreases the number of elements by 8.25% compared to the conventional Mills cross multiplicative array, while keeping the advantages of narrow main lobe width and low sidelobe level. Improved genetic algorithm is an effective method for the underwater acoustic imaging array to implement the sparse optimization.
Authors with CRIS profile
Involved external institutions
China (CN)How to cite
APA:
Teng, D., Li, Y., Yang, H., Wei, Z., & Li, Y. (2022). Genetic Algorithm for Sparse Optimization of Mills Cross Array Used in Underwater Acoustic Imaging. Journal of Marine Science and Engineering, 10(2). https://dx.doi.org/10.3390/jmse10020155
MLA:
Teng, Duo, et al. "Genetic Algorithm for Sparse Optimization of Mills Cross Array Used in Underwater Acoustic Imaging." Journal of Marine Science and Engineering 10.2 (2022).
BibTeX: Download