摘要
对于高精度GPS定位,应用传统的载波相位平滑伪距算法会使定位的连续性和精度受到影响,在高动态GPS环境中甚至无法正常应用.基于标准卡尔曼滤波算法假设,利用极大似然准则推导了一种新的应用于载波相位平滑伪距的自适应卡尔曼滤波算法,这种滤波算法利用新息序列分别对系统过程噪声方差和量测噪声方差进行实时估计和调整,得到适用于动态定位的载波相位平滑伪距所需的最优平滑时间常数.在相关理论分析的基础上,对自适应卡尔曼滤波算法的稳定性进行了分析.动态定位仿真结果表明,与传统的载波相位平滑伪距算法相比,自适应卡尔曼滤波算法可以有效改善定位的精度和稳定性.
In the high precision of GPS positioning,dynamical positioning case limits the performance of traditional carrier smoothed code in terms of consistency and accuracy.In some extreme conditions,it even cannot work normally.According to the maximum likelihood estimation criterion,a new adaptive Kalman filtering algorithm for carrier smoothed code is proposed in this paper.The innovation sequences are used to timely estimate and adjust the variance of system noise and measurement noise,respectively,and then an optimal smoothing time constant suitable for carrier smoothing in dynamic positioning is derived from the adaptive algorithm.Based on the theoretical analysis,the stability of the adaptive Kalman filtering algorithm is analyzed.The simulation results show that the adaptive Kalman filtering algorithm for carrier smoothed code outperforms the traditional carrier smoothed code in improving the precision and stability.
出处
《哈尔滨工程大学学报》
EI
CAS
CSCD
北大核心
2010年第12期1636-1641,共6页
Journal of Harbin Engineering University
基金
国际科学技术工业委员会基础研究基金资助项目(08J3.8.8)
国家自然科学基金资助项目(60474046)
