基于小波神经网络的PIM功率时间序列预测

无源互调（passive intermodulation，PIM）是影响通信系统性能的关键因素之一。研究表明，PIM信号并非一个定值，而是随时间变化的非平稳信号。基于PIM功率信号的时间序列特性，文章提出基于小波神经网络的PIM功率时间序列预测方法。首先，详细介绍小波神经网络预测模型及其预测方法；其次，以同轴连接器为验证对象，通过PIM实验测试系统获得3阶PIM功率的时间序列；最后，依据获得的PIM功率时间序列，结合构建的小波神经网络预测模型对后续的时间序列进行预测分析，并将预测结果与实验结果进行比较，从而验证小波神经网络在预测PIM功率时间序列方面的有效性。该研究对于开展PIM抑制技术具有一定的参考价值。

Prediction of passive intermodulation based on wavelet neural network

Passive intermodulation is one of the key factors which have an influence on the performance of communication systems. It is found that the PIM signal is not a fixed value, but a non-stationary signal which varies with time. With the characteristic of time series of PIM signal, a predicting method on PIM power is proposed based on wavelet neural network in this paper. Firstly, the predicting model and its predicting method on wavelet neural network are described in detail. Secondly, as the verification object, the coaxial connector is chosen and the time series of third-order PIM power is obtained through the PIM testing system. Lastly, predicting model based on the wavelet neural network is used to predict the subsequent PIM power with the obtained time series. And it is verified that the wavelet neural network has a good performance on predicting PIM power by comparing the predicted results and experimental results. This study is helpful to develop suppression technology on PIM.