基于飞行数据的无人机平飞动作质量评价模型

针对无人机（UAV）操纵质量高低多依赖专家主观评判、不同飞行动作缺乏针对性评判标准的问题，建立了根据飞行数据客观评价无人机平飞动作质量的模型。首先通过建立平飞判别规则识别无人机飞行数据中的平飞动作数据段，然后根据布林通道理论计算各平飞数据段内多个飞行参数的得分值，最后通过"熵权法"确定各参数的权重，进而得到反映不同无人机操控手平飞动作质量的指标数据。将一次四边平飞训练任务中4组不同无人机操控手操纵和1组无人机自主控制的飞行数据输入该模型，计算结果表明，模型可以较好地识别平飞动作并区分不同操控手平飞动作质量的高低，可以为无人机操控手的训练提供参考。 

Quality evaluation model of unmanned aerial vehicle's horizontal flight maneuver based on flight data

The unmanned aerial vehicle (UAV) manipulator's flying performance mostly relies on experts' subjective evaluation and different flight maneuvers lack pertinent evaluation criteria, so a model which uses flight data to evaluate the horizontal flight quality of UAV is established. Firstly, the flight data segment of UAV's horizontal flight maneuver was identified by the flight discrimination rules. Then, according to Bollinger bands theory, the scores of multiple flight parameters in each flight data segment were calculated. Finally, the weight of each parameter was determined by the entropy weight method and the indexes reflecting the horizontal flight maneuver's quality of different UAV manipulators were obtained. In a quadrilateral flying training mission, four groups of different UAV maneuvers' flight data and one group of flight data under autonomous control were input into the model. The calculation results show that the model can well identify the horizontal flight maneuver and distinguish the horizontal flight maneuver's quality of different manipulators, which can provide advice for the training of UAV manipulators.