微分截断误差的遥、外测数据融合估计和补偿方法研究

The studying of a fusion approach to estimate and compensate the differential truncation error using tracking and telemeted data

通过对定位数据求微分以获得目标的速度参数,是靶场估计目标运动参数的常用方法。由于坐标参数模型的高阶特性,使得在通过对坐标数据微分求速度参数时,产生较大的微分截断误差。仅靠外测数据本身,是无法估计该误差的。该文提出了利用遥、外测数据融合估计该截断误差并予以补偿的方法,可有效估计速度参数求解时的方法误差,从而提高参数估计的精度。

Using position data to obtain velocity parameters of object through differential coefficient is a general method in range.Because of the high step of coordinate model,it will be bring a biggish truncation errors when differential the coordinate data to obtain the velocity parameters.It is unable to estimate the truncation errors just use the tracking data only.This paper proposed a method to estimate and compensate the differential truncation error using tracking and telemeted data.The simulation demonstrates the method can estimate the technique error effectively and improve the parameters estimate accuracy greatly.