初级教练机中的低成本导航仪组合导航算法设计

为了解决初级教练机低成本组合导航仪中全球定位系统(GPS, Global Positioning System)信息更新频率过低,导致传统组合导航算法失效的问题,在对惯性器件进行建模的基础上,提出了一种基于运动学非线性模型的组合导航算法.该算法选取载体的姿态、速度和位移量作为状态量,以GPS、磁强计和高度计的测量值作为观测量,建立组合导航系统模型,利用卡尔曼滤波对线性化后的系统模型进行数据融合.通过静态试验和动态跑车试验,表明该组合导航算法能够使姿态误差均值控制在0.12°以内,速度误差均值不大于0.03m/s,位移量误差均值不大于3.94m,精度能够满足初级教练机的应用需要.

Integrated navigation algorithm for low-cost navigator in the primary trainer

To solve the invalidation of integrated navigation algorithm due to low updating frequency of global positioning system (GPS) in the low-cost integrated navigation system, a new integrated navigation algorithm, based on modeling of the inertial devices and kinematic modeling of the carrier, was presented. In this algorithm, the nonlinear system model was established. The attitude, velocity and position of the carrier were chosen to be the system state, and the output of the GPS, gauss meter, and altimeter were determined as the system measurement. The Kalman filter was adopted for data fusion after linearization of the system model. The static test and field test were implemented to validate whether the algorithm was useful. The test results show that the algorithm can effectively ensure that the error mean of attitude is smaller than 0.12 degree, the error mean of velocity is not larger than 0.03 meters per second, and the error mean of position is not larger than 3.94 meters, which is satisfied the requirement of the primary trainer.