移动平滑算法在无人机遥测数据处理中的应用

Moving-Polynomial Smoother Algorithm for Telemetry Flight-Test Data Processing of Pilotless Helicopter

研究了用于无人机飞行试验数据事后处理的平滑滤波及预报问题 .提出白噪声多项式的最优线性移动平滑滤波算法应用于分离飞行遥测数据中的真实信号和随机噪声 ,并通过滤波方差比给出对随机误差的压缩程度 .试验结果表明 ,该方法对各种飞行数据有效、可靠、适用 .

Method of filtering and smoothing of the telemetry flight-test data post-processing of no-driver helicopter is discussed here. An optimal linear polynomial filter with white noise moving-polynomial algorithm is proposed to estimate the true values from telemetry signals with random noise. The degree of compression for the random error is provided by the variance ratio of filtering. The algorithm was used to post-process some actual flight test data and the results confirmed the adaptability and effectiveness of this method.