Science and Technology on Inertial Laboratory, Beijing 100191, China.
Sensors (Basel). 2012 Sep 27;12(10):13212-24. doi: 10.3390/s121013212.
This paper presents an adaptive information fusion method to improve the accuracy and reliability of the altitude measurement information for small unmanned aerial rotorcraft during the landing process. Focusing on the low measurement performance of sensors mounted on small unmanned aerial rotorcraft, a wavelet filter is applied as a pre-filter to attenuate the high frequency noises in the sensor output. Furthermore, to improve altitude information, an adaptive extended Kalman filter based on a maximum a posteriori criterion is proposed to estimate measurement noise covariance matrix in real time. Finally, the effectiveness of the proposed method is proved by static tests, hovering flight and autonomous landing flight tests.
本文提出了一种自适应信息融合方法，以提高小型无人旋翼机在着陆过程中高度测量信息的准确性和可靠性。针对小型无人旋翼机上传感器测量性能低的问题，应用小波滤波器作为预滤波器，以衰减传感器输出中的高频噪声。此外，为了提高高度信息，提出了一种基于最大后验概率准则的自适应扩展卡尔曼滤波器来实时估计测量噪声协方差矩阵。最后，通过静态测试、悬停飞行和自主着陆飞行测试验证了所提出方法的有效性。
