自适应Kalman滤波在光纤陀螺SINS/GNSS紧组合导航中的应用

为了提高光纤陀螺捷联惯性导航系统（SINS）和全球卫星导航系统（GNSS）的组合导航精度和系统稳定性，设计了基于伪距、伪距率的紧组合导航系统模型。针对光纤陀螺的白噪声特点，以及误差不稳定性导致无法精确建模，将残差引入误差方差阵的估计中，提出了一种改进的自适应卡尔曼滤波方法。采用改进的自适应卡尔曼滤波方法滤波得到导航参数的最优估计，然后对系统进行反馈补偿校正，抑制了滤波发散问题，提高了系统的稳定性。稳态测试试验结果表明:设计的光纤陀螺SINS/GNSS 紧组合导航系统具有较好的鲁棒性；在三颗卫星的条件下，系统能够在短期内保持较高的导航精度，验证紧组合导航的优越性。

Fiber optic gyroscope SINS/GNSS tight integrated navigation based on adaptive Kalman filter

In order to advance tight integrated navigation precision and stability of fiber optic gyroscope (FOG) strap-down inertial navigation system(SINS) and globe navigation satellite system(GNSS), a SINS/ GNSS tight integrated navigation system was designed based on pseudo range and pseudo range rate. For the white Gaussian noise of FOG and instability of error statistics and model, the residual error was calculated in the evaluation of error variance matrix, an improved adaptive Kalman filtering method was proposed. Optimal estimation of navigation parameters were obtained with the improved adaptive Kalman filtering method, and system was corrected with feedback compensation. Then the divergence of Kalman filtering was well restrained and the stability of the system was enhanced. Through the static test, the results demonstrate that the designed fiber optic gyroscope SINS/GNSS system has good robustness. Under the condition of three navigation satellites, system could maintain nice navigation accuracy that verifies the excellence of tight integrated navigation.