针对激光陀螺(RLG)随机误差严重影响初始对准精度并且国内没有成熟的激光陀螺随机误差模型的问题,采用Burg算法建立激光陀螺随机误差自回归模型,根据上述模型实现激光陀螺随机误差在惯导系统应用中的在线建模,采用卡尔曼滤波技术实现实时滤波。利用Allan方差比较滤波结果,滤波前后随机误差系数均减少了50%。实验结果表明:该方法大大提高了RLG捷联惯导系统的对准精度以及缩短了对准时间。 Aiming at the problem that the random errors of laser gyro (RLG) seriously affect the initial alignment accuracy and there is no mature laser gyro random error model in our country, Burg algorithm is used to establish a laser gyro random error autoregressive model. According to the above model, System application of online modeling, using Kalman filter technology to achieve real-time filtering. Using Allan variance comparison filter results, the random error coefficients before and after filtering are reduced by 50%. Experimental results show that this method greatly improves the alignment accuracy and shortens the alignment time of RLG SINS.