基于强跟踪GHF的里程计辅助SINS动基座对准研究

为提高车载捷联惯导系统动基座初始对准精度,提出了一种强跟踪降维高斯-厄米特非线性动基座初始对准算法。里程计辅助捷联惯导粗对准后水平姿态误差角为小角度,里程计辅助捷联惯导动基座对准模型简化为大方位失准角非线性模型,采用降维高斯-厄米特滤波(GHF),以少数非线性状态积分点估计整个系统状态,减少计算量,应用强跟踪滤波,提高系统对突变的滤波状态的跟踪能力。实验表明,应用强跟踪降维高斯-厄米特滤波提高了动基座初始对准精度,减少了计算量,提高了滤波的稳定性。

Research on the Moving SINS Initial Alignment Method Based on Strong Tracking Gauss Hermite Filter With OD Aiding

In order to improve the vehicle moving alignment accuracy of the strapdown inertial navigation system, the moving initial alignment algorithm is proposed based on the nonlinear Gauss Hermite filter (GHF) with the strong tracing and dimensionality reduction. Based on OD aiding, the horizontal attitude error of coarse alignment is a small angle, and the SINS moving initial alignment model is simplified to be large azimuth misalignment angle nonlinear model. Based this model, the dimensionality of nonlinear Gauss Hermite filter can be reduced, the status of the system can be estimated with a few nonlinear integral points, and the amount of calculation decrease. Also, the strong tracing method is applied to improve the tracking ability of the mutation filter status. With the experiment, the Gauss Hermite nonlinear moving alignment scheme with the strong tracing and dimensionality reduction can improve the precision of the moving alignment, decrease the amount of calculation and improve the stability of the filtering.