基于XGBoost的无人机测温误差分析
Analysis of Temperature Measurement Error of Unmanned Aerial Vehicle Based on XGBoost

采用无人机监测海温时，由于无人机的飞行高度、横滚角、俯仰角、航向角、航速等姿态以及所处环境，采集的温度值与实际值存在一定的误差，将上述影响红外测温精度的因素考虑在内，采用机器学习中的XGBoost进行温度预测与测温误差分析，预测出较为理想的温度值，并得出了影响测温误差的关键因素。
Under the influence of the flying height of the UAV, the roll angle, the pitch angle, the direction an-gle, the speed and so on, the temperature values of the UAV have some error. The factors affecting the infrared temperature measurement accuracy are taken into consideration, and the XGBoost into the machine learning is adopted. The temperature prediction and the error analysis of tem-perature measurement are used to predict the ideal temperature value, and the key factors af-fecting the error of temperature measurement are obtained.？