基于容错卡尔曼滤波的校验无人机精确测高法

Precise altitude measuring method of flight-inspecting UAV based on fault-tolerant Kalman filter

针对旋翼无人机多机载高度传感器中传感器信号突变导致融合高度信息误差较大的问题,提出了一种基于容错卡尔曼滤波(FTKFT)的高度精确测量方法。该测量方法包括1个主滤波器和3个子卡尔曼滤波器(GPS/气压高度计/超声波高度计),利用卡尔曼滤波器对各高度传感器进行滤波并计算其高度估计值与误差值作为检测信号,以惯导短时间内二次积分作为参考信号,通过检错器进行状态卡方检测与残差卡方检测。最后,基于每个高度传感器的输出误差通过加权的方法实现多高度传感器的最优数据融合。仿真和飞行实验验证了该方法的测量精度及实时容错性能够满足校验要求。

In UAV fixed-point flight verification, the real-time height measurement accuracy determines the angle verification error of PAPI (precision approach path indicator). Aiming at the large information error of fusion height caused by signal mutation of rotor UAV multi-airborne height sensor, a precise height measuring method based on FTKFT (fault-tolerant Kalman filter) is proposed consisting of a main Kalman filter and three sub-filters (GPS/barometric altimeter/radar altimeter). Each height sensor is filtered by Kalman filter, calculating the height estimation and the error as detecting signal and the second-order integration of inertial navigation in short time as reference signal, conducting state Chi-square test and residual Chi-square test with error detector. Finally, optimal data fusion of multi height sensors basing on output error of each height sensor is realized with weighting. Simulation and flight experiment show that this method is capable to achieve the expected measuring accuracy and real-time fault-tolerant performance.