基于容错卡尔曼滤波的校验无人机精确测高法
|
摘要
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.
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.
引文
[1]中国民用航空局机场司.机场设计手册[M].北京:中国民用航空局,2004:58-66.
[2]中国民用航空局.飞行校验规则[G].北京:中国民用航空局, 2000.
[3]中国民用航空局.民用机场飞行区技术标准[G].北京:中国民用航空局, 2013.
[4]胡永红.数据融合方法在小型高度定位中的应用[J].计算机测量与控制, 2006, 14(10):1371-1373.
[5] DRAK A, NOURA H, HEJASE M, et al. Sensor fault diagnostic and fault-tolerant control for the altitude control of a quadrotor UAV[C]//2015 IEEE 8th GCC Conference and Exhibition(GCCCE), IEEE, 2015:1-5.
[6] GENG K K, CHULIN N A. Applications of multi-height sensors data fusion and fault-tolerant kalman filter in integrated navigation system of UAV[J]. Procedia Computer Science, 2017, 103:231-238.
[7]浦黄忠,胡磊,王道波.无人机高精度容错高度测量系统设计[J].传感器与微系统, 2007, 26(8):84-86.
[2]中国民用航空局.飞行校验规则[G].北京:中国民用航空局, 2000.
[3]中国民用航空局.民用机场飞行区技术标准[G].北京:中国民用航空局, 2013.
[4]胡永红.数据融合方法在小型高度定位中的应用[J].计算机测量与控制, 2006, 14(10):1371-1373.
[5] DRAK A, NOURA H, HEJASE M, et al. Sensor fault diagnostic and fault-tolerant control for the altitude control of a quadrotor UAV[C]//2015 IEEE 8th GCC Conference and Exhibition(GCCCE), IEEE, 2015:1-5.
[6] GENG K K, CHULIN N A. Applications of multi-height sensors data fusion and fault-tolerant kalman filter in integrated navigation system of UAV[J]. Procedia Computer Science, 2017, 103:231-238.
[7]浦黄忠,胡磊,王道波.无人机高精度容错高度测量系统设计[J].传感器与微系统, 2007, 26(8):84-86.