基于卡尔曼滤波算法卫星数不足情况下的连续定位

摘要

The Kalman filtering model was introduced in this paper. And it was used as a parameter estimation method to realize dynamic pseudo-range single positioning solutions. It also resolved partial observations with insufficient visible satellites. And the positioning results were compared. The test result indicates that Kalman filer model help to keep positioning continuously and guarantee a certain extent precision.%介绍了卡尔曼滤波模型,采用C#编程语言建立了程序模块,并将其作为参数估计方法对一组动态数据进行了伪距单点定位解算；将部分历元时刻卫星数设置为少于4颗进行解算,并比较了其定位结果与原始结果的差异.实验结果表明,采用卡尔曼滤波模型能够在卫星数不足的情况下在一定时间内保持定位的连续性,并能保证一定精度.