摘要
GNSS/IMU组合导航一般采取基于欧拉角的组合方式。为了加快收敛速度,通常采用非线性滤波。但非线性滤波如EKF等仍然有一定的截断误差且计算量较大。采取基于DCM的组合导航方式,建立了基于DCM的GNSS/IMU的组合导航模型,并以基于DCM的卡尔曼滤波方式进行滤波解算。组合导航姿态收敛快,且计算量小。通过采用无人机实测数据进行分析,并与基于欧拉角的Kalman滤波组合导航算法进行比较,该方法有效缩短了计算时间,且精度较高。更适合无人机等高动态载体的实时导航需求。
GNSS / IMU integrated navigation is generally based on Euler angles. And non-linear filtering is usually used to speed up the convergence rate. However, the non-linear filtering such as EKF still has a certain truncation error and the calculation amount is large. A new kind of integrated navigation based on DCM was adopted here to build GNSS / IMU integrated navigation, and Kalman filtering based on DCM was used to filter and calculate data.The convergence rate of attitude of this integrated navigation is fast and the computation is small. The algorithm was analyzed by using the real data of UAV during the experiment. And compared with the Kalman filtering algorithm based on Euler angles, this method is more accurate and less computational. It is more suitable for real-time navigation needs of high dynamic carrier such as UAV.
出处
《测绘科学技术学报》
CSCD
北大核心
2016年第1期16-20,共5页
Journal of Geomatics Science and Technology
基金
地理信息工程国家重点实验室重点基金课题(SKLGIE2014-Z-2-1)
