无人机自适应平滑切换姿态融合算法研究

On UAV Attitude Estimation Algorithm Combination with Adaptive Smooth Switching

针对GPS信号丢失导致组合导航算法精度降低甚至发散的难题,开展一种高效的自适应平滑切换融合算法研究。在GPS信号正常情况下,采用基于GPS量测的高阶组合导航算法估计姿态信息;在GPS信号丢失时,停止高阶滤波算法并切换为基于四元数的低阶姿态估计算法;当GPS信号恢复后,将低阶姿态估计算法的估计值作为高阶滤波算法初值,实现姿态估计算法的平滑切换。仿真结果和试飞试验表明,该切换策略具有较好的估计精度和可实现性,且切换过程中姿态角跳变小于0.5°,收敛时间小于0.1 s,有效地提高了有、无GPS信号情况下无人机的姿态估计精度。

When GPS signals are lostthe accuracy of the integrated navigation algorithm will decrease.To solve the probleman efficient adaptive smooth switching fusion algorithm is proposed.When the GPS signal is under normal conditionsa high-order integrated navigation algorithm based on GPS measurement is used to estimate UAV attitude.When the GPS signal is lostthe high-order filtering algorithm is terminated and switched to a low-order attitude estimation algorithm based on quaternion.When the GPS signal is restoredthe estimated value of the low-order attitude estimation algorithm is taken as the initial value of the high-order filtering algorithmso as to realize smooth switching between the two attitude estimation algorithms.Simulation results and flight tests show that the switching strategy has good estimation accuracy and feasibilityattitude angle jumping is less than 0.5°during the switching processand the convergence time is less than 0.1 swhich effectively improve the accuracy of UAV attitude estimation with or without GPS signals.