双层梯度蜂窝吸波结构优化设计

Optimization Design of Double-Layer Grading Honeycomb Absorbing Structure

关键词:  梯度设计  双层蜂窝结构  吸波材料  反射率  优化设计  阻抗匹配  保收敛粒子群优化算法

Key words:  Grading design  Double-layer honeycomb structure  Radar absorbing material  Reflection coefficient  Optimization design  Impedance matching  Guarantee convergence particle swarm optimization

摘要:

为了提高蜂窝结构的吸波特性，设计了一种带蒙皮和金属底板的双层梯度蜂窝吸波结构，并利用Hashin-Shtrikman（HS）模型获得其等效电磁参数。在此基础上，以反射率低于-10dB的带宽最大为优化目标，利用保收敛粒子群优化算法（Guarantee Convergence Particle Swarm Optimization，GCPSO）对四种不同排序方案的双层梯度蜂窝吸波结构进行优化设计。结果表明，入射电磁波的角度和极化方式以及吸波材料的选择、排序和厚度对双层梯度蜂窝结构的吸波性能有很大的影响；不同入射角度下Transverse Magnetic （TM）极化时的吸波特性明显优于Transverse Electric （TE）极化，在入射角为60°时最为明显；对比四种方案优化结果显示，Case 1方案由于选用损耗角较小的吸波材料充当透波层，分布于蒙皮下面，而选用损耗角较大的吸波材料作吸收层，并置于吸波结构底层，因而具有最大的优化目标函数，吸波效果最佳，且蜂窝高度仅为具有相同吸波效果的Case 3方案的49.44%。因此，选择Case 1方案作为本文最终优化结果。

Abstract:

In order to improve the absorbing characteristics of the honeycomb structure， adouble-layer grading honeycomb radar absorbing structure （RAS） with skin and metal base plate was designed， and its equivalent electromagnetic parameters were obtained by using Hashin-Shtrikman （HS） model. Then， the Guarantee Convergence Particle Swarm Optimization （GCPSO） was adopted for the optimization design of the double-layer grading honeycomb RAS with four different material ordering schemes， and the optimization objective was to maximize the bandwidth with the reflection coefficient below -10dB. The results show that the angle and polarization of the incident electromagnetic wave as well as the selection， order and thickness of the radar absorbing materials （RAM） have great effects on the absorbing performance of the double-layer grading honeycomb RAS. The absorption characteristics under Transverse Magnetic （TM） polarization are better than that of Transverse Electric （TE） polarization at different incident angles， which is most obvious when the incident angle is 60°. The comparison of the optimization results of the four schemes shows that in Case 1， the RAM with small loss angle is selected as the transmission layer and distributed under the skin， while the RAM with large loss angle is selected as the absorbing layer， which is placed at the bottom of the grading honeycomb RAS. Therefore， Case 1 has the largest objective function value and better absorbing performance， and the height of the honeycomb structure is only 49.44% of that of Case 3， which has similar absorbing characteristics. Based on this， the result of Case 1 is selected as the final optimization result of this paper.