基于多项式回归的无人机监测数据分析及预测

Analysis and Prediction of UAV Monitoring Data Based on Polynomial Regression

利用无人机进行某系统数据监测,得到不同的载机高度、载机速度、测试角度以及不同的目标高度和目标速度下测试到的离目标对象的最大值。已知无人机系统监测得到的52×104条记录数据,其中包括无人机在载机高度为1~11km、载机速度50~130km/h、进入角为0°~180°时测试得到的离目标对象的最大值。本文针对已知数据,利用机器学习的算法建立多项式回归模型,可以预测出在无人机在任意高度,任意角度和任意载机速度下得到的最大值,且分别针对不同的多项式预测结果进行比对,选取误差最小的为最终模型。

UAV is used for data monitoring of a certain system,and obtain the maximum distance from the target object tested under different carrier altitudes,carrier speeds,test angles,and different target altitudes and target speeds.It is known that 520,000recorded data obtained by the UAV system monitoring,including the UAV at an altitude of 1-11 kilometers,a speed of 50-130kilometers per hour,and an angle of 0-180 degrees.Based on the known data,this paper uses the machine learning algorithm to establish a polynomial regression model,which can predict the maximum value obtained by the UAV at any height,any angle,and any carrier speed,and carry out different polynomial prediction results respectively.For comparison,the model with the smallest error is selected as the final model.