Navigation Research Center, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
Sensors (Basel). 2019 Oct 8;19(19):4337. doi: 10.3390/s19194337.
In this paper, a drag model-aided fault-tolerant state estimation method is presented for quadrotors. Firstly, the drag model accuracy was improved by modeling an angular rate related item and an angular acceleration related item, which are related with flight maneuver. Then the drag model, light detection and ranging (LIDAR), and inertial measurement unit (IMU) were fused based on the Federal Kalman filter frame. In the filter, the LIDAR estimation fault was detected and isolated, and the disturbance to the drag model was estimated and compensated. Some experiments were carried out, showing that the velocity and position estimation were improved compared with the traditional LIDAR/IMU fusion scheme.
本文提出了一种用于四旋翼飞行器的基于阻力模型辅助的容错状态估计方法。首先，通过对与飞行机动相关的角速率相关项和角加速度相关项进行建模，提高了阻力模型的精度。然后，基于联邦卡尔曼滤波器框架，将阻力模型、激光雷达（LIDAR）和惯性测量单元（IMU）进行融合。在滤波器中，检测和隔离了 LIDAR 估计故障，并对阻力模型的干扰进行了估计和补偿。一些实验表明，与传统的 LIDAR/IMU 融合方案相比，速度和位置估计得到了改善。
