航天测量事后数据处理多尺度融合算法  

Multi-scale Fusion Algorithm for Data Processing after Aerospace Measure Mission

作　　者：任松[1] 

机构地区：[1]西昌卫星发射中心技术部,四川西昌615000

出　　处：《信息与电子工程》2007年第5期325-328,共4页information and electronic engineering

摘　　要：针对国内航天测量事后数据处理的现状,提出了一种基于Kalman滤波的数据处理多尺度融合算法。该算法以建立的系统动态模型方程为基础,归纳出多尺度融合算法的具体步骤,通过实际算例验算,结果表明:融合尺度越小,数据处理精度改善的效果越明显,并且与α-β-γ滤波算法相比,数据处理精度也有较大提高。According to the actuality of data processing after aerospace measure mission in China, an algorithm of multi-scale data fusion for data processing based on Kalman filter is put forward. On the basis of system dynamic model equation, idiographic steps of the algorithm are concluded. Through the verification using an actual example, the result indicates that the algorithm is very effective and the precision of processing will be improved more evidently as the fusion scale is more smaller. Contrasted with α-β-γfilter algorithm, the precision of data processing of the fusion algorithm is boosted markedly.

关 键 词：航天测量 数据处理 多尺度融合算法 KALMAN滤波 

分 类 号：V447.1[航空宇航科学与技术—飞行器设计]