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

陳志坤; 杜康; 彭冬亮; 朱新挺

doi:10.11999/JEIT190705

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

杭州電子科技大學(xué)自動化學(xué)院杭州 310018

基金項目: 國家自然科學(xué)基金(61701148)

詳細信息

作者簡介:
陳志坤：男，1982年生，博士，講師，研究方向為雷達陣列信號處理與電子偵察

杜康：男，1996年生，碩士生，研究方向為陣列優(yōu)化與波束形成

彭冬亮：男，1977年生，博士，教授，博士生導(dǎo)師，研究方向為信息融合

朱新挺：男，1996年生，碩士生，研究方向為信號檢測技術(shù)

通訊作者:
杜康　dk@hdu.edu.cn

中圖分類號: TN957.2
計量
- 文章訪問數(shù): 2810
- HTML全文瀏覽量: 888
- PDF下載量: 74
- 被引次數(shù): 0
出版歷程
- 收稿日期: 2019-09-10
- 修回日期: 2019-11-28
- 網(wǎng)絡(luò)出版日期: 2020-01-11
- 刊出日期: 2020-06-04

Planar Sparse Array Constraint Optimization Based on Hybrid Trigonometric Mutation Differential Evolution Algorithm

School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China

Funds: The National Natural Science Foundation of China (61701148)

摘要

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。
- 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.
- Sparse array optimization /
- Differential Evolution (DE) algorithm /
- Adaptive penalty function /
- Side lobe nulls

HTML全文

圖 1 稀疏陣列3維方向圖

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圖 2 算法收斂曲線對比和稀疏陣元分布

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圖 3 可行解比例和$u = 0$比平面方向圖

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圖 4 稀疏陣列3維方向圖

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圖 5 算法收斂曲線和稀疏陣元分布

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圖 6 可行解比例和$u = 0$平面方向圖

下載: 全尺寸圖片幻燈片

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

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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

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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

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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

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