基于混合三角變異差分進化算法的平面稀疏陣列約束優(yōu)化
doi: 10.11999/JEIT190705
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杭州電子科技大學(xué)自動化學(xué)院 杭州 310018
Planar Sparse Array Constraint Optimization Based on Hybrid Trigonometric Mutation Differential Evolution Algorithm
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School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
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摘要:
針對旁瓣零陷凹面約束的稀疏平面陣列優(yōu)化及算法早熟等問題,該文基于參數(shù)自適應(yīng)的思想,提出一種混合三角變異差分進化算法。通過引入旁瓣零陷凹面約束矩陣,構(gòu)建自適應(yīng)懲罰函數(shù),時變權(quán)重組合變異策略與交叉策略,提高算法前期全局搜索能力和后期收斂能力,最終實現(xiàn)峰值旁瓣電平和旁瓣零陷凹面的平面陣列約束優(yōu)化。仿真結(jié)果表明,對比混合三角變異策略前的算法,該算法在完成稀疏陣列峰值旁瓣電平優(yōu)化的同時,能在指定旁瓣區(qū)域完成零陷凹面設(shè)計,降低有源干擾影響。
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關(guān)鍵詞:
- 稀疏陣列優(yōu)化 /
- 差分進化算法 /
- 自適應(yīng)懲罰函數(shù) /
- 旁瓣零陷
Abstract:For the problems of sparse planar array optimization with side-lobe concave nulls constraints and premature algorithm, a Hybrid Trigonometric Mutation Differential Evolution (HTMDE) algorithm is proposed based on the idea of parameter adaptation. By introducing side-lobe concave nulls constraints matrix, adaptive penalty function is constructed. Time-varying weight combination mutation strategy and crossover strategy improve the initial global search ability and late convergence ability of the algorithm. The constrained optimization of the planar array with peak side lobe level and side-lobe concave nulls is finally realized. The simulation results show that, compared with the algorithm before the hybrid trigonometric mutation strategy, the algorithm not only optimizes the peak side-lobe level of sparse array, but also designs concave nulls in specified side-lobe area to reduce the influence of active interference.
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表 1 最大零陷深度約束為45時旁瓣零陷凹面增益(c = 1)
序號 1 2 3 4 5 6 7 8 9 $p$ 50 50 50 51 51 51 52 52 52 $q$ 50 51 52 50 51 52 50 51 52 增益(dB) –41.7232 –47.8437 –43.4869 –41.2586 –53.0450 –44.7019 –43.8560 –46.1852 –46.9309 下載: 導(dǎo)出CSV
表 2 最大零陷深度約束為50時旁瓣零陷凹面增益(c = 1)
序號 1 2 3 4 5 6 7 8 9 $p$ 50 50 50 51 51 51 52 52 52 $q$ 50 51 52 50 51 52 50 51 52 增益(dB) –46.6703 –45.7740 –42.0270 –43.5748 –55.1658 –43.9545 –42.9269 –49.6869 –45.4186 下載: 導(dǎo)出CSV
表 3 最大零陷深度約束為55時旁瓣零陷凹面增益(c = 1)
序號 1 2 3 4 5 6 7 8 9 $p$ 50 50 50 51 51 51 52 52 52 $q$ 50 51 52 50 51 52 50 51 52 增益(dB) –46.4656 –47.1974 –43.3241 –47.4544 –58.0909 –43.7558 –55.5215 –48.7782 –45.2064 下載: 導(dǎo)出CSV
表 4 最大零陷深度約束為45時旁瓣零陷凹面增益(c = 2)
序號 1 2 3 4 5 6 7 8 9 p 49 49 49 49 49 50 50 50 50 q 49 50 51 52 53 49 50 51 52 增益(dB) –46.5458 –45.8412 –46.2580 –40.8917 –40.9214 –49.3585 –55.9305 –47.3353 –42.1900 序號 10 11 12 13 14 15 16 17 18 p 50 51 51 51 51 51 52 52 52 q 53 49 50 51 52 53 49 50 51 增益(dB) –42.6126 –43.5500 –51.2554 –49.3633 –44.1652 –43.3289 –44.5767 –60 –60 序號 19 20 21 22 23 24 25 p 52 52 53 53 53 53 53 q 52 53 49 50 51 52 53 增益(dB) –45.5003 –42.0649 –46.5876 –45.0475 –48.2879 –44.7265 –41.0207 下載: 導(dǎo)出CSV
表 5 最大零陷深度約束為50時旁瓣零陷凹面增益(c = 2)
序號 1 2 3 4 5 6 7 8 9 p 49 49 49 49 49 50 50 50 50 q 49 50 51 52 53 49 50 51 52 增益(dB) –37.6175 –40.3846 –45.7498 –48.2500 –43.6255 –36.8799 –41.7660 –49.6858 –45.8806 序號 10 11 12 13 14 15 16 17 18 p 50 51 51 51 51 51 52 52 52 q 53 49 50 51 52 53 49 50 51 增益(dB) –41.8181 –37.2718 –43.5080 –60 –45.8777 –39.6356 –39.5716 –45.9265 –60 序號 19 20 21 22 23 24 25 $p$ 52 52 53 53 53 53 53 $q$ 52 53 49 50 51 52 53 增益(dB) –47.8587 –39.4033 –43.4406 –50.7166 –60 –51.4716 –40.3799 下載: 導(dǎo)出CSV
表 6 最大零陷深度約束為55時旁瓣零陷凹面增益(c = 2)
序號 1 2 3 4 5 6 7 8 9 p 49 49 49 49 49 50 50 50 50 q 49 50 51 52 53 49 50 51 52 增益(dB) –44.8401 –46.0399 –39.5838 –38.3594 –45.4208 –54.4196 –59.5659 –43.2692 –43.0806 序號 10 11 12 13 14 15 16 17 18 p 50 51 51 51 51 51 52 52 52 q 53 49 50 51 52 53 49 50 51 增益(dB) –51.9257 –41.3720 –45.5307 –55.5682 –49.6248 –40.8617 –36.9498 –40.1514 –48.4430 序號 19 20 21 22 23 24 25 $p$ 52 52 53 53 53 53 53 $q$ 52 53 49 50 51 52 53 增益(dB) –43.0303 –37.3386 –35.2466 –38.9316 –46.3749 –42.4130 –37.3552 下載: 導(dǎo)出CSV
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