基于非线性滤波算法的GPS与北斗定位研究

GPS-BDS Positioning Research Based on Nonlinear Filter Algorithm

全球导航卫星系统GNSS可以提供全天时的三维位置信息和三维速度信息。传统只靠单一的导航系统不能满足系统的可靠性和完善性。为此提出GPS系统与北斗导航系统兼容定位方法,描述了测量模型和状态模型,并使用平淡卡尔曼滤波进行定位解算,在GPS和北斗导航系统环境下分别进行了单系统和多系统定位的验证、比较与分析。定位实验结果表明,与通用的最小二乘迭代法和扩展卡尔曼滤波等方法获得的结果相比,所提出的算法能获得更高的定位精度。当可见卫星数量发生跳变时,得出的滤波结果具有较高的精度和稳定性,特别是在卫星数比较少的情况下,通过组合两个不能单独定位的系统,可获得更高的融合定位精度。

Global Navigation Satellite System can provide all-day three-dimensional position and speed information. Currently single navigation system only cannot meet the needs of system＇ s reliability and integrity. BDS and GPS navigation system positioning method was presented, the measurement model and the state model were described. Furthermore, Unscented Kalman Fiher （UKF） was employed in GPS and BDS conditions, and analyses of single system and multi-systems＇ positioning were carried out respectively. The experimental results were compared with the estimation results obtained by the iterative least square method and the extended Kalman filtering method, h shows that the proposed method performs higher positioning precision, when the visible satellite number changes, the filtering results of this algorithm of have higher accuracy and stability. Especially when the number of satellites is net enough, the proposed method can combine BDS and GPS systems to carry out a higher positioning precision.