基于自适应衰减因子Kalman滤波的GPS相位平滑伪距算法  

Algorithm of GPS phase smoothing pseudo-range based on adaptive attenuation factor Kalman filtering

作　　者：崔法毅[1] 解文肖 

机构地区：[1]燕山大学河北省测试计量技术及仪器重点实验室,河北秦皇岛066004

出　　处：《红外与激光工程》2015年第1期377-383,共7页Infrared and Laser Engineering

基　　金：秦皇岛市科学技术研究与发展计划(2012021A004)

摘　　要：载波相位平滑伪距的主要目的是通过高精度的载波相位测量值作为辅助量,使伪距测量值中、大随机误差得以消减。针对GPS伪距测量中未知时变的噪声,提出基于极大后验时变噪声统计估计器的自适应衰减因子Kalman滤波算法(AFKF),采用衰减的加权因子,使估计器逐渐忘记陈旧数据的作用,同时增加新数据的比重,避免滤波过程的发散。结合载波相位平滑伪距原理,利用AFKF算法对全球导航卫星系统(GNSS)的国际GNSS服务组织(IGS)的跟踪站实测数据进行仿真分析,并提出利用伪距双差值及伪距三差值来直观体现不同算法的效果比较,结果表明:与标准Kalman滤波相比,AFKF算法在伪距平滑应用中取得很好的效果。The main purpose of carrier phase smoothing pseudo- range is to reduce large random error of pseudo- range measurement values, by using high- precision carrier phase measurement values as the supplementary information. In view of the unknown time - varying noise in GPS pseudo - range measurement, an algorithm of adaptive attenuation factor kalman filter （AFKF） was put forward, which was based on maximum a posteriori （MAP） time- varying noise statistical estimator. In order to avoid the divergence of filtering process, the effect of old data could be gradually forgotten by using estimator with attenuation weighted factors, while the proportion of new data could be increased. Simulation analysis was carried out on the measured data of tracking station of a International Global Navigation Satellite System Service （IGS）, by using the AFKF algorithm combining with carrier phase smoothing pseudo- range principle. And the double differential and the three differential pseudo- ranges were proposed to intuitively reflect the effects of different algorithms. Experimental results show that the AFKF algorithm can obtain better effect in application of pseudo- range smoothing, compared with the standard KF algorithm.

关 键 词：全球定位系统 相位平滑伪距 极大后验估计 自适应衰减因子卡尔曼滤波 

分 类 号：P228.4[天文地球—大地测量学与测量工程]