卫星拒止情况下低精度惯导系统航姿算法研究

在卫星拒止情况下,低精度MEMS惯导系统由于惯性器件性能较差,无法长时间保持姿态精度。从重力矢量及飞行器的动力学特性出发,提出了一种基于动态检测和Kalman数据融合的航姿算法。该算法从导航与飞控一体化的理念出发,实时判断飞行器机动和飞控状态,在低动态时利用Kalman滤波器对水平加速度和惯性解算的姿态角进行数据融合,估计和修正水平姿态误差,从而提高水平姿态精度。经过飞行仿真验证,该算法可有效完成飞行器的动态检测,并保证在系统机动情况下水平姿态误差在2°以内。

Research on Attitude and Heading Reference Algorithm of Low-accuracy INS in GNSS Denial Environment

In GNSS denied environment, the low-precision MEMS inertial navigation system cannot maintain attitude accuracy for a long time due to the poor performance of the inertial devices. Based on the gravity vector and the dynamic characteristics of the aircraft, this paper proposes a heading algorithm based on dynamic detection and Kalman data fusion. Based on the concept of integrated navigation and flight control, the algorithm judges the aircraft maneuvering and flight control status in real time, and uses Kalman filter to fuse the data of horizontal acceleration and inertial attitude angle at low dynamics to estimate and correct horizontal attitude error, thereby improving horizontal attitude accuracy. After the flight test simulation verification, the algorithm can effectively complete the dynamic detection of the aircraft and ensure that the horizontal attitude error of the system is within 2° under the condition of maneuvering.