基于双惯导协同的误差参数估计与融合算法

Error parameter estimation and fusion algorithm based on dual inertial navigation coordination

针对无外界参考信息的双惯导系统长期使用后系统参数发生变化导致导航精度降低,且系统间缺少信息融合的问题,提出了一种同等精度双惯导协同误差估计与信息融合算法。首先以两套旋转式惯导间相对速度误差与位置误差作为观测量,建立包含陀螺和加速度计零偏的导航误差模型。然后分析了不同转序下各状态量的可观测性,采用Kalman滤波对各参数进行有效估计,估计完成后对双惯导系统进行误差补偿及信息融合。仿真结果表明,所提算法对陀螺零偏估计精度优于0.002(°)/h,加速度计零偏估计精度优于4μg,在抑制误差发散的同时,提高了旋转式惯导导航精度。

In order to solve the problem that the inertial navigation accuracy decreases which caused by the parameters changing of dual inertial navigation systems(INSs)after a long period without external information and the dual INSs lack the information fusion between systems,an error estimation and information fusion algorithm for dual INSs with equal accuracy is proposed.Firstly,the relative velocity error and position error between dual rotating INSs are used as observation variables,and the navigation error model including gyro and accelerometer biases is established.Then,the observability of each state under different rotation sequence is analyzed,and Kalman filtering method is used to estimate various parameters effectively.After the estimation is completed,error compensation and information fusion are carried out for dual INSs.The simulation results show that the estimated accuracy of the proposed algorithm is better than 0.002()/h°for the gyro bias and better than 4μg for the accelerometer bias of dual inertial navigation system,which can restrain the error divergence and improve the navigation accuracy of rotating INS.