基于模糊自适应卡尔曼滤波的平滑伪距算法  

Algorithm of Carrier Smoothed Code Based on Fuzzy Adaptive Kalman Filtering

作　　者：康德功 谢刚[1] 程兰[1] 

机构地区：[1]太原理工大学信息工程学院,山西太原030024

出　　处：《计算机仿真》2014年第5期385-388,401,共5页Computer Simulation

基　　金：山西省太原市2012年科学技术发展计划大学生创新创业专题(120164013);太原市2012年科学技术发展计划电子信息及物联网产业专题(111102)

摘　　要：研究导航定位精度优化问题,针对传统的载波相位平滑伪距算法在较多历元数时精度误差较大,而补充卡尔曼滤波的相位平滑伪距算法的噪声变化无法动态估计等不足,提出了一种基于模糊自适应卡尔曼滤波的相位平滑伪距算法。本算法根据观测噪声的新息与协方差的均值变化,对时变的噪声统计特性实时估计与调整,达到最优估计,以增加滤波的时效性、提高定位精度。仿真结果表明,该算法在状态估计上精度更高,并且抑制噪声的稳定性更高,定位精度优于传统的载波相位平滑伪距算法和基于补充卡尔曼滤波的相位平滑伪距算法。As the accuracy of the carrier smoothed code is not high when the number of epochs is large in traditional methods of carrier smoothed code, and the noise changes cannot be estimated dynamically in complementary Kalman filtering. An algorithm of carrier smoothed code based on the fuzzy adaptive Kalman filtering was proposed in this paper. According to the average change of new interest rates and the covariance of the observation noise, the time -varying noise statistical characteristics were estimated and adjusted in real time to achieve the optimal estimation, increase the efficiency of the filter, and improve the positioning accuracy. The experimental results ＇show that the algorithm has not only higher state estimation precision, but also higher noise stability. The positioning accuracy is more superior in both the accuracy and the stability to the traditional carrier smoothed code and the method based on complementary Kalman filtering.

关 键 词：高精度定位 差分定位 相位平滑伪距 模糊卡尔曼滤波 

分 类 号：TN967.1[电子电信—信号与信息处理]