基于多模型最优融合的双星定位系统一体化精密定轨方法

针对卫星动力学模型复杂且不准,考虑到卫星定轨中待估参数在时间和空间上的相关性,提出了一种基于多模型最优融合的双星定位系统一体化参数建模的近地卫星精密定轨新方法．利用节点自由分布B样条描述卫星运动,实现了对卫星粗略动力学模型的抑制作用;同时结合双星观测模型,使该方法转化为关于求解卫星轨道样条表示参数和定轨系统误差的多模型融合的非线性优化问题;通过引入模型结构确定最优融合权值的选取准则,在最小二乘准则下,采用非线性最优化方法搜寻样条的最优节点分布,得到了待估参数的最优估计,完成了近地卫星的精密定轨．理论分析和仿真计算表明,该方法确实有效,不仅提高了卫星的定轨精度,而且使状态估计的结构更加稳定．

Optimal Multi-Model Merging Method for Integrative Satellite Precise Orbit Determination Based on GEOSTAR System

Considering the complexity and inaccuracy of the dynamic model for satellite and the fact that parameters to be estimated in orbit determination are correlated temporally with each other, an optical multi-model merging method for integrative satellite precise orbit determination based on GEOSTAR system is proposed. The B-spine function with knots-free is adopted to describe the motion state of a satellite and thus to realize the reduction the error of the dynamic model. Combining the bi-satellite distance observation model, the precise trajectory determination process can be transformed into a nonlinear optimization problem of the multi model merging with the parameters of orbit spine expression coefficients and observation system error coefficients. By introducing the model structure to determinate the selection rule of optimal merging weight and adopting the nonlinear optimization method under LSE rule to search the optimal spine knots distribution, the optimal estimation for the parameters to-be-estimated can be obtained, and the more precise determination of the LEO can be completed. The theoretical analysis and simulation show that this method is more effective, not only in increasing the ultimate precision of satellite state, but also in making the structure of state estimation more robust.