基于随机耦合模型的腔体电磁耦合快速计算

Fast evaluation of cavity electromagnetic coupling based on the random coupling model

  • 摘要: 针对外部辐射源照射腔体结构时耦合观测端口频繁变化的场景,提出了一种结合辐射阻抗矩阵与扩展随机耦合模型的电磁耦合统计结果快速计算方法。计算模型在结构上由一副喇叭发射天线和一个位于发射天线远场区且具有耦合孔缝与耦合观测端口的四旋翼无人机组成。按照扩展随机耦合模型,通过传输矩阵建立了相应的传输线等效分析模型以便获得随机耦合模型所需的腔体阻抗与损耗参数。进一步,采用辐射阻抗矩阵计算了耦合观测端口处的感应电压概率密度函数,该结果与平均阻抗矩阵以及全波仿真结果所得的统计结果具有良好的一致性。相比于平均阻抗矩阵,辐射阻抗矩阵计算耗时少,有利于扩展随机耦合模型对复杂腔体电磁耦合统计结果的快速计算。

     

    Abstract:
    Background Electromagnetic coupling is a key link that governs the effect of the high-power microwave on drones. Efficient computation of electromagnetic coupling benefits the elucidation of the laws of electromagnetic coupling and the proposal of measures for coupling manipulation.
    Purpose To achieve rapid evaluation of electromagnetic coupling for a quadcopter illuminated by an external antenna in scenarios where the coupling observation ports change frequently, a method combining the radiation impedance matrix with the extended random coupling model is presented.
    Methods The involved model structurally consists of a transmitting horn antenna and a quadcopter positioned in the far-field region of the transmitting antenna. The quadcopter features coupling apertures and a coupling observation port. According to the extended random coupling model, a corresponding transmission-line equivalent model is established through the transmission matrix to obtain the cavity impedance and loss parameter necessary for the random coupling model.
    Results Furthermore, the radiation impedance matrix is employed to calculate the probability density function of the induced voltage at the coupling observation port. The obtained results are in good agreement with the statistical results derived from the average impedance matrix and from full-wave simulations.
    Conclusions Compared with the average impedance matrix, the radiation impedance matrix is temporally less expensive, thereby facilitating the rapid evaluation of electromagnetic coupling statistics for complex cavities using the extended random coupling model.

     

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