基于SR-UKF的高动态GPS信号参数估计  

Parameter Estimation of Highly Dynamic GPS Signal based on Square Root Unscented Kalman Filter

作　　者：杨少委[1] 张旭东[1] 

机构地区：[1]电子科技大学电子科学技术研究院,四川成都610054

出　　处：《通信技术》2010年第9期9-11,共3页Communications Technology

摘　　要：高动态环境下,全球定位系统(GPS)信号具有较强的非线性特性,为了更好地对高动态条件下的GPS信号载波进行跟踪,提出了一种基于平方根UKF(SR-UKF)算法的高动态GPS信号参数估计方法。分析了高动态环境下GPS信号载波相位模型,运用SR-UKF算法对高动态GPS信号的载波相位及其前三阶导数进行估计。仿真对比了SR-UKF、不敏卡尔曼滤波(UKF,Unscented Kalman Filter)和扩展卡尔曼滤波(EKF)载波跟踪算法的性能。仿真结果表明,SR-UKF的估计精度要好于EKF,与UKF基本一致,验证了该算法的可靠性和有效性。GPS signal has strong nonlinear characteristics under highly dynamic circumstance.For tracking the highly dynamic GPS carrier,an algorithm based on the square root Unscented Kalman filter （UKF） is proposed to estimate the parameters of highly dynamic GPS signal.The model of highly dynamic GPS carrier phase is analyzed.The SR-UKF estimator is designed for the phase and its first three-order derivatives of GPS signal in highly dynamic circumstance.For comparison with UKF and EKF,SR-UKF is simulated with MATLAB.The simulation result shows that the estimation precision of SR-UKF is better than that of EKF and the same as that of UKF,and the algorithm is feasible and efficient.

关 键 词：高动态 平方根不敏卡尔曼滤波 全球定位系统 参数估计 

分 类 号：TN967.1[电子电信—信号与信息处理]