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中文摘要：
为实现遥测数据的快速和高精度预测,针对遥测数据的非平稳性特点,提出一种基于小波分析和自适应指数平滑法的建模方法.该方法引入小波分析技术对遥测数据非平稳序列进行分解和重构,将原始非平稳遥测数据序列分解为较平稳的序列.利用对传统的指数平滑法改进后的自适应指数平滑法和周期自回归模型（PAR模型）建立短期预测模型,并对太阳翼输出功率数据的未来趋势进行预测分析.实验结果表明预测曲线与实际曲线吻合效果理想,该方法能够有效的解决遥测数据的短期预测问题.
英文摘要：
In order to achieve fast and high-precision prediction for telemetry data, according to the non-stationary of telemetry data, a forecast method based on wavelet analysis and adaptive exponential smoothing is proposed. Wavelet analysis technology is used to make decomposition and reconstruction for non-stationary sequence and steady sequence is obtained. Then adaptive exponential smoothing that is improved from traditional exponential smoothing and periodic autoregressive model （ PAR model ） are used to build shortterm prediction model, and the model is used to analyze the data of solar array output power. Simulation results show that predict curve and practical curve are almost coincide, the method is effective to solve the short-term forecasting problem of telemetry data.
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