Introduction to the Kalman-Schmidt Filter

This article provides an insight into the application of the Kalman-Schmidt filter to navigation for technical
personnel with limited background in probability theory. The scope of the article includes the statistical derivation of the Kalman-Schmidt filter within the context of spaceflight navigation. The filter may be used to locate a space vehicle and to determine its velocity vector from data containing random errors. The filter is superior to least squares because each observation datum does not have to determine the position of the vehicle.