基于ARMA模型的受损限幅器模型建立方法

杨晓炜; 张海

doi:10.11884/HPLPB201931.190238

基于ARMA模型的受损限幅器模型建立方法

doi: 10.11884/HPLPB201931.190238

杨晓炜^{1, 2,},
张海^{1, 2, ,}

1.
中国工程物理研究院电子工程研究所，四川绵阳 621900
2.
中国工程物理研究院复杂电磁环境重点实验室，四川绵阳 621900

基金项目: 中国工程物理研究院复杂电磁环境重点实验室基金项目

详细信息

作者简介:
杨晓炜(1988-), 男, 硕士, 从事雷达信号分析及数值仿真研究; yangxwh@126.com

通讯作者:
张海(1968-), 男, 博士, 研究员, 从事雷达信号分析及效应数值仿真研究; e2zhanghai@aliyun.com

中图分类号: TN911
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- 被引次数: 0
出版历程
- 收稿日期: 2019-06-27
- 修回日期: 2019-08-28
- 刊出日期: 2019-10-15

Auto-regressive moving average modeling algorithm of impaired limiter

Yang Xiaowei^{1, 2
,},
Zhang Hai^{1, 2
, ,}

1.
Institute of Electronic Engineering, CAEP, Mianyang 621900, China
2.
Complicated Electromagnetic Environment Laboratory of China Academy of Engineering Physics, Mianyang 621900, China

摘要

摘要: 针对限幅器遭受功能或物理损伤而发生的非线性效应, 给出了一种基于信号分析的受损限幅器非线性效应研究新视角, 并从该视角出发, 提出了模型建立方法。该方法首先测得受损限幅器幅频响应序列, 将其转化为零均值实平稳序列; 然后计算该序列的自相关函数和偏相关函数, 估计自回归滑动平均(ARMA)模型的阶数; 最后采用最小二乘法估计出模型的表达式, 并采用最终预测误差(FPE)准则对该表达式进行校验。试验结果和理论分析验证了该方法的良好效果。
- 非线性效应 /
- 限幅器 /
- ARMA模型 /
- 复杂电磁环境
Abstract: A new perspective of the impaired limiter based on signal analysis is presented for the nonlinear effect of the limiter subjected to functional or physical damage.For this perspective, the modeling algorithm is proposed.Firstly, an amplitude-frequency response sequence of the impaired limiter is measured, and converted into a zero-mean real stationary sequence.Then, the autocorrelation function and the partial autocorrelation function of the sequence are calculated along with the estimated order of the auto-regressive moving average(ARMA)model which is estimated by least squares method, and verified by the Final Prediction Error(FPE)criterion.Experiment results agree well with theoretical analysis.
- nonlinear effect /
- limiter /
- ARMA model /
- complicated electromagnetic environment

HTML全文

图 1 基于ARMA模型的受损限幅器模型建立流程图

Figure 1. Flow chart of ARMA modeling process of impaired limiter

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图 2 试验中用的限幅器

Figure 2. Limiters used in experiment

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图 3 受损限幅器的幅频响应序列图

Figure 3. Amplitude-frequency response sequence of impaired limiter

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图 4 增量序列样本图

Figure 4. Differential sequence

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图 5 增量序列样本自相关函数和样本偏相关函数

Figure 5. Sample autocorrelation function and sample partial autocorrelation function of differential sequence

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图 6 FPE函数值与阶数关系

Figure 6. FPE vs p

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图 7 根分布图

Figure 7. Root map

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图 8 增量序列的原始响应与模型响应

Figure 8. Original response vs model response

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表 1 概率结果

Table 1. Table of probability

p	P_MA/%	P_AR/%	p	P_MA/%	P_AR/%
1	15.79	73.68	6	7.14	85.71
2	11.11	72.22	7	7.69	92.31
3	11.76	76.47	8	8.33	100.00
4	12.50	75.00	9	9.09	100.00
5	13.33	80.00	10	10.00	100.00

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参考文献(10)

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