一种适用于惯性-地磁组合的自适应卡尔曼算法-计算机工程与应用.PDF

Computer Engineering and Applications 计算机工程与应用 2018 ，54（3 ） 57 一种适用于惯性-地磁组合的自适应卡尔曼算法 用 1 2 戎海龙 ，彭翠云 应 1 2 RONG Hailong ，PENG Cuiyun 与 1.常州大学 城市轨道交通学院，江苏 常州 213164 程 2.常州大学 信息科学与工程学院，江苏 常州 213164 g r 1.School of Urban Rail Transmit, Changzhou University, Changzhou, Jiangsu 213164, China 工 o 2.School of Information Science Engineering, Changzhou University, Changzhou, Jiangsu 213164, China . 机 j a RONG Hailong ，PENG Cuiyun. Adaptive Kalman filter used for inertial- magnetic units. Computer Engineering 算 e and Applications, 2018, 54 （3 ）：57-63. c 计 w. Abstract ：There is a common problem existed in the existing attitude algorithm used for inertial-magnetic units, that is, some of those depend too much on the outputs of gyro, and have good dynamic but poor static performance, while the w other of those depend too much on the outputs of Accelerometer and Geomagnetic sensor （AG ）, and have good static but w poor dynamic performance. It is problematic to use the module of the linear acceleration to regulate the dependence of gyro or AG, though it is sometimes effective. A method proposed in this paper is to estimate the module of the linear acceleration vector and the geomagnetic vector, and then takes the estimation error as the observation noise of the Extended Kalman Filter （EKF ）, which is the most commonly used in the attitude algorithm, in order to construct an adaptive EKF. The estimation error is zero-mean and stationary, and most importantly, its variance