Unmanned aerial vehicle state estimation method, system and device and readable storage medium

The invention provides an unmanned aerial vehicle state estimation method. The method comprises the following steps: establishing a system model; according to the system model, at a specified moment, prediction of state estimation of standard extended Kalman and initialization of iteration extended Kalman filtering estimation into standard extended Kalman filtering estimation are carried out; and executing Taylor expansion of an estimation point estimated by the standard extended Kalman filter, and carrying out iteration updating calculation of specified times of measurement. The stability and reliability of the flight state of the unmanned aerial vehicle are improved, and development and popularization of the unmanned aerial vehicle industry are further promoted. 本发明提供了一种无人机状态估计方法，所述方法包括：建立系统模型；根据系统模型，在指定时刻，进行标准扩展卡尔曼的状态估计的预测以及初始化迭代扩展卡尔曼滤波估计为标准扩展卡尔曼滤波估计；执行在标准扩展卡尔曼滤波估计的估计点的泰勒展开，并进行量测的指定次数的迭代更新计算。本发明提高了无人机飞行状态的稳定性和可靠性，进一步促进无人机行业的发展与普及。