火箭飞行数据分布式多尺度融合的研究

A Study on Multiscale Distributed Data Fusion for Measurement Data from Launch Vehicle

结合我国现阶段航天测量体制,提出了一种分布式无反馈结构的多尺度融合算法,这是一个基于标准Kalman滤波的最优算法,适用于卫星发射任务事后的数据处理.给出了雷达实测数据的算例,算例结果表明,提出的分布式多尺度融合算法处理精度比传统的αβγ滤波处理精度有较大改善,尺度越小,改善效果越明显.

According to Chinese telemeter and telecommand （TT＆C） system, a multiscale distributed fusion without feedback was presented for analyzing measurement data from launch vehicles. This is an algorithm based on standard Kalman filtering, and it can be used in measurement data processing after satellite launching missions. The examples of measurment data were processed by using the algorithm. The results show that the processing accuracy by using the algorithm is better than the one by using traditional α-β-γ The smaller the scale,the more evident effect becomes.