基于改进滑动时间窗口的国产民用飞机APM参数筛选研究

合适的飞行性能监测（APM）参数筛选方法可实现国产民用巡航飞机性能监控参数的高效筛选，为飞机性能分析计算提供可靠的数据基础。在无迹卡尔曼滤波（UKF）中引入 Sage-Husa 噪声估计器，构造自适应无迹卡尔曼滤波（AUKF），利用 AUKF 对快速存取记录器（QAR）数据进行降噪；给出稳定巡航参数筛选的标准，采用改进滑动时间窗口算法对稳定巡航参数进行筛选，并通过国产 ARJ21 飞机的样本数据进行验证。结果表明：自适应无迹卡尔曼滤波算法能够提高数据的可靠性，改进滑动时间窗口算法使筛选效率提高约 50%。

Research on aircraft performance monitoring parameter selection based on improved window algorithm

In order to improve the screening efficiency of domestic civil aircraft performance monitoring parameters, a method based on improved sliding time window is proposed to screen stable cruise parameters. Unscented Kalman filter (UKF) introduces sage husa noise estimator, constructs adaptive unscented Kalman filter (AUKF), and uses AUKF to denoise QAR data; The selection standard of cruise parameters is determined, the recursive algorithm improves the sliding time window algorithm and realizes the selection of cruise parameters, and the GUI develops the parameter selection system to further improve the efficiency of parameter selection. Through the sample data of domestic ARJ21 aircraft, the results showed that AUKF can improve the reliability of data, and the improved sliding time window algorithm can improve the screening efficiency by about 50%. The research can provide reliable and efficient data selection algorithm basis for domestic civil aircraft performance monitoring parameter selection.