Feature analysis of atmosphere laser communication channel under rainy condition based on WFET

It is difficult to analyze atmosphere laser communication channel(ALCC) under rainy condition with traditional mathematics methods. Weights feature extracting technology(WFET), as a novel data analysis tool to extract training data sets´ feature information from weight sets in the trained multi-layer perceptron network(MLPN), is proposed, which can achieve in-depth analysis in data sets. Firstly, atmosphere laser communication experimental data sets are adopted to construct training data sets of MLPN. Secondly, train the MLPN with the data sets, and the feature information will transfer into MLPN adequately after training process. Thirdly, extract feature information from trained MLPN with WFET, which can calculate weights energy channels and correlations in data sets. Actual tests show that season´s correlation is stronger than rainfall, and the rain intensity´s correlation is stronger than season and rainfall factors. The result is an important reference of ALCC under rainy condition.