自适应逐次逼近的粗时段导航算法

Coarse-time navigation algorithm based on adaptive successive approximation

针对粗时段导航中粗时误差较大导致线性化误差较大从而定位精度差,以及五状态粗时段导航DOP比四状态导航大的问题,提出一种自适应逐次逼近的粗时段导航算法:采取每次迭代更新状态、逐次逼近,并自适应推入四状态导航重新解算的方法,以得到较高的定位精度。实验结果表明,该算法能够在各粗时误差下获得与常规四状态导航接近的较高精度的定位结果。

Aiming at the problems that the positioning accuracy is poor with large linearization error due to coarse time errors in coarse-time navigation,and the DOPs in five-state coarse-time navigation are higher than those in four-state navigation,the paper proposed a coarse-time navigation algorithm based on adaptive successive approximation:the state of every iteration was update by approximating successively,and the four-state navigation was adaptively pushed in to re-calculate for obtaining a high positioning accuracy.Experimental result showed that the proposed algorithm could get a high positioning accuracy similar to that of normal four-state navigation with different coarse time errors.