Analysis and prediction of electromagnetic interference behavior level in power distribution network of UAV positioning system
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摘要: 电源分配网络是无人机定位系统工作的基础单元，也是电磁干扰薄弱环节，电源分配网络（PDN）传导耦合干扰效应是导致定位系统故障的主要原因。为了提高定位系统电磁干扰敏感度预测模型的精度，基于泰勒级数对非线性系统的描述方法，将泰勒级数行为级模型系数表征为与干扰频率相关的函数，建立无人机定位系统PDN电磁干扰响应预测模型，分析预测PDN在受干扰情况下的非线性直流偏置电压。研究结果表明：在250～400 MHz电磁干扰范围内，基于泰勒级数的PDN电磁干扰响应预测模型可以对PDN在电磁干扰作用下的非线性直流偏置进行准确预测，预测误差在3%以内。Abstract: Power distribution network is the basic unit of unmanned aerial vehicle (UAV) positioning system, but also the weak link of electromagnetic interference (EMI). The conduction coupling interference effect of power distribution network (PDN) is the main cause of positioning system failure. To improve the accuracy of positioning system sensitivity of electromagnetic interference prediction model, based on the Taylor series description method for nonlinear systems, the Taylor series behavior level model coefficient is characterized as interference frequency related function, thus a UAV positioning system PDN electromagnetic interference response prediction model is established, which analyzes and predicts PDN’s nonlinear dc bias voltage under the circumstance of interference. The results show that the Taylor series based PDN EMI response prediction model can accurately predict the nonlinear DC bias of PDN under 250−400 MHz EMI, and the prediction error is within 3%.
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图 2 定位系统电源分配网络结构实物图
Figure 2. Structure of the power distribution network of UAV positioning system
图 3 基于泰勒级数的非线性系统行为级模型原理图
Figure 3. Behavior level model of nonlinear system based on Taylor series
图 7 泰勒级数行为级响应预测模型系数与干扰频率关系图
Figure 7. Relationship between the coefficients of Taylor series behavior-level response prediction model and interference frequency
表 1 电源分配网络EMI响应理论与实测误差对比表
Table 1. Comparison between theoretical and measured values of EMI response in power distribution network
forward
power/dBminterference
frequency/MHzDC component
measurement value/VDC component
predicted value/Verror/% −36.7 250 3.29 3.2005 2.72 −33.2 250 3.26 3.2003 1.83 −30.1 250 3.19 3.1999 0.31 −38.0 310 3.13 3.1205 0.30 −34.9 310 3.17 3.1200 1.57 −31.3 310 3.06 3.1200 1.96 −38.3 400 2.98 2.9899 0.33 −37.5 400 2.98 2.9898 0.33 −39.4 400 2.99 2.9900 $ 5.2 \times {10^{ - 4}} $ 
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