基于衰减记忆高斯和滤波的星间精密测距技术  

Precise Intersatellite Ranging Technique Based on Fading Memory Gaussian Sum Filtering

作　　者：李理敏[1,2] 马陆[1,2] 任前义[1] 余金培 

机构地区：[1]上海微小卫星工程中心,上海200050 [2]中国科学院上海微系统与信息技术研究所,上海200050

出　　处：《电子与信息学报》2011年第2期295-299,共5页Journal of Electronics & Information Technology

基　　金：上海市自然科学基金(10ZR1429100);上海市优秀学科带头人计划(08XD14038)资助课题

摘　　要：星间精密测距是导航星座实现自主导航的核心技术。针对导航星座中码测量值精度低但无整周模糊度,载波相位测量值精度高但存在整周模糊度的特点,该文根据贝叶斯递推原理提出了一种衰减记忆高斯和滤波(Fading Memory Gaussian Sum Filter,FMGSF)的伪距估计方法。该方法用高斯和形式近似表示系统后验概率密度,并根据卡尔曼滤波原理来更新高斯项的均值和方差,同时引入衰减记忆因子克服由于模型失配导致的滤波结果发散问题,利用重采样解决由于载波相位测量值不确定导致的算法复杂度增加问题。理论分析和仿真结果表明,该文提出的方法不仅能够克服周跳对伪距估计的影响,而且可以获得更好的测距精度。Precise ranging is the core technology of autonomous navigation.For code measurements yield noisy but unambiguous pseudorange estimates and the pseudorange obtained with carrier phase measurements are almost noiseless but are affected by integer ambiguity,a Fading Memory Gaussian Sum Filter（FMGSF） algorithm based on Bayesian recursive relations is proposed.Posteriori probability density is approximated as a finite Gaussian mixture,the means and variances of Gaussian terms are updated according to the principle of Kalman filter.Fading memory factor is imported to avoid the issue of filter divergence due to mismodeling and resampling is performed to resolve the issue of increasing in computational complexity caused by carrier phase measurement uncertainty.Theoretical analysis and simulation results show that this algorithm can overcome the effect of cycle slips to a certain extent and achieve higher range accuracy.

关 键 词：卫星间精密测距 衰减记忆 高斯和滤波 HATCH滤波 周跳 

分 类 号：TN927.3[电子电信—通信与信息系统]