基于罗德里格斯参数的惯性系传递对准算法

针对传统的传递对准模型在大失准角下的强非线性问题以及由残余杆臂误差导致的传递对准精度下降问题, 提出了一种改进的惯性系传递对准算法。首先, 对子惯导姿态矩阵进行链式分解, 得到常值姿态矩阵; 然后, 利用罗德里格斯参数等价替代该常值姿态矩阵, 建立关于罗德里格斯参数和残余杆臂误差的具有弱非线性量测的传递对准模型; 最后, 利用非线性滤波对状态进行估计。基于摇摆运动的仿真实验表明, 在存在大安装误差角以及残余杆臂误差情况下, 算法相比于现有方法, 对准速度更快, 对准精度更高, 在5~10 s内即可完成传递对准。车载试验结果也间接说明算法具有更高的传递对准性能。

Inertial-frame-based transfer alignment using Rodriguez parameters

Aiming at the strong nonlinear problem for the conventional transfer alignment model with large misalignment angle and the problem of the degraded alignment accuracy induced by the residual lever arm error, an improved inertial-frame-based transfer alignment (ITA) method is proposed for inertial navigation system (INS). Firstly, a constant attitude matrix is obtained based on the chain rule for the attitude matrix of slave INS. Then, the constant attitude matrix is equivalently replaced by the Rodriguez parameter, and a novel transfer alignment model with weakly nonlinear measurement equation is established based on the Rodriguez parameter and the residual lever arm error. Finally, the nonlinear Kalman filters are implemented for the estimation. Simulation results under the sway motion illustrate that when the installation error angles are large and the residual lever arm error exists, the ITA method has the faster alignment speed and the better alignment accuracy than existing transfer alignment methods, and the transfer alignment can be completed in 5~10s. The field test results also illustrate that the ITA method has significantly better alignment performance.