Infrared and Laser Engineering, Volume. 53, Issue 12, 20240339(2024)
Optical phased array multi-objective gate optimisation based on improved population algorithm
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Fig. 2. Comparison of the light field of a uniform array and a random array. (a) Uniform; (b) Random
Fig. 3. Schematic of the objective function. (a) Scan range; (b) Side-mode suppression ratio
Fig. 4. Scenario 1 multi-objective grid optimisation scenario flow
Fig. 5. Iteration result graph. (a) Function 1; (b) Function 2; (c) Function 3; (d) Iterative optimal rendering of function 3
Fig. 6. Optimization graph of function 2. (a) Deflection angle change; (b)
Fig. 7. Comparison chart of three multi-objective methods to optimize iterations
Table 1. Optimization results of edge-mode rejection ratio in different array ranges
View tableView in ArticleTable 1. Optimization results of edge-mode rejection ratio in different array ranges
Array range/μm FSMSR of function 1/dB FSMSR of function 2/dB FSMSR of function 3/dB 1-3 −21.33 −19.57 −18.60 2-5 −15.95 −16.11 −14.29 5-8 −13.65 −13.60 −13.38
Table 2. The results of the optimization of different multi-objective methods
View tableView in ArticleTable 2. The results of the optimization of different multi-objective methods
Method FSMSR /dB FIOL Time/s Multi-HHO −16.11 4061 218 NSGA-Ⅱ −15.00 4015 182 Weighted sum −13.89 4219 12 NSGA-Ⅲ −15.00 4093 108 MOEA-D −13.91 4116 127 MOPSO −14.66 3845 112 SPEA2 −14.09 4185 111
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Yijun HUANGFU, Muchun ZHOU. Optical phased array multi-objective gate optimisation based on improved population algorithm[J]. Infrared and Laser Engineering, 2024, 53(12): 20240339
Paper Information
Category: 激光器与激光光学
Received: Jul. 23, 2024
Accepted: --
Published Online: Jan. 16, 2025
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