UKF在高动态GPS数据处理中的应用  

Application of UKF in High Dynamic GPS Data Processing

作　　者：黄斌 胡俊 高迎彬[3] 张会会 

机构地区：[1]第二炮兵工程大学,陕西西安710025 [2]广东省有色地质测绘院,广东广州510080 [3]第二炮兵驻石家庄地区军事代表室,河北石家庄050081

出　　处：《无线电工程》2016年第4期47-51,共5页Radio Engineering

摘　　要：针对高动态GPS数据处理中的非线性问题,提出了一种基于无迹卡尔曼滤波(UKF)的非线性GPS数据处理方法。传统的方法是将滤波中的非线性方程在标称轨道附近采样线性化,这样会产生较大的误差且计算较难实现。所提算法利用UKF处理GPS数据模型中的非线性方程,采用加权采样点的高斯最小集来表示状态分布,然后通过U变换产生的状态变量进行滤波估计。仿真实验表明,所提算法能够有效处理高动态GPS数据中的非线性问题,预测精度也有较大提高。In order to overcome the effects of nonlinearity in high dynamic GPS data processing,a nonlinear GPS data processing method based on Unscented Kalman Filter（UKF） is proposed. In traditional method, the nonlinear equation is linearized by sampling near the nominal trajectory ,which, however, may lead to relatively large error and high computation complexity.The proposed method u- ses the weighted sampling points to represent the state distribution when processing the nonlinear equation, then performs filtering esti- mation through the variants generated by U-transformation.Simulation experiment shows that the UKF is effective in solving the nonlin- earity issue of high dynamic GPS data,and it also improves the prediction accuracy.

关 键 词：无迹卡尔曼滤波 高动态 GPS 

分 类 号：TP911.72[自动化与计算机技术]