基于混合三角变异差分进化算法的平面稀疏阵列约束优化

陈志坤; 杜康; 彭冬亮; 朱新挺

doi:10.11999/JEIT190705

基于混合三角变异差分进化算法的平面稀疏阵列约束优化

doi: 10.11999/JEIT190705

杭州电子科技大学自动化学院杭州 310018

基金项目: 国家自然科学基金(61701148)

详细信息

作者简介:
陈志坤：男，1982年生，博士，讲师，研究方向为雷达阵列信号处理与电子侦察

杜康：男，1996年生，硕士生，研究方向为阵列优化与波束形成

彭冬亮：男，1977年生，博士，教授，博士生导师，研究方向为信息融合

朱新挺：男，1996年生，硕士生，研究方向为信号检测技术

通讯作者:
杜康　dk@hdu.edu.cn

中图分类号: TN957.2
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- 被引次数: 0
出版历程
- 收稿日期: 2019-09-10
- 修回日期: 2019-11-28
- 网络出版日期: 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:
针对旁瓣零陷凹面约束的稀疏平面阵列优化及算法早熟等问题，该文基于参数自适应的思想，提出一种混合三角变异差分进化算法。通过引入旁瓣零陷凹面约束矩阵，构建自适应惩罚函数，时变权重组合变异策略与交叉策略，提高算法前期全局搜索能力和后期收敛能力，最终实现峰值旁瓣电平和旁瓣零陷凹面的平面阵列约束优化。仿真结果表明，对比混合三角变异策略前的算法，该算法在完成稀疏阵列峰值旁瓣电平优化的同时，能在指定旁瓣区域完成零陷凹面设计，降低有源干扰影响。
- 稀疏阵列优化 /
- 差分进化算法 /
- 自适应惩罚函数 /
- 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

图 1 稀疏阵列3维方向图

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图 2 算法收敛曲线对比和稀疏阵元分布

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图 3 可行解比例和$u = 0$比平面方向图

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图 4 稀疏阵列3维方向图

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图 5 算法收敛曲线和稀疏阵元分布

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图 6 可行解比例和$u = 0$平面方向图

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表 1 最大零陷深度约束为45时旁瓣零陷凹面增益(c = 1)

序号	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

下载: 导出CSV

表 2 最大零陷深度约束为50时旁瓣零陷凹面增益(c = 1)

序号	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

下载: 导出CSV

表 3 最大零陷深度约束为55时旁瓣零陷凹面增益(c = 1)

序号	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 最大零陷深度约束为45时旁瓣零陷凹面增益(c = 2)

序号	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
序号	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
序号	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

下载: 导出CSV

表 5 最大零陷深度约束为50时旁瓣零陷凹面增益(c = 2)

序号	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
序号	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
序号	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

下载: 导出CSV

表 6 最大零陷深度约束为55时旁瓣零陷凹面增益(c = 2)

序号	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
序号	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
序号	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

下载: 导出CSV

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