Application of Kalman filtering to spacecraft range residual predictionOne function of the Deep Space Network is validation of the range data that they receive. In this paper we present an automated online sequential range predictor which shows promise of significantly reducing computational and manpower expenditures. The proposed algorithm, a U-D covariance factored Kalman filter, is demonstrated by processing a four-month record of Viking spacecraft data taken enroute to Mars.
Document ID
19780059123
Acquisition Source
Legacy CDMS
Document Type
Conference Proceedings
Authors
Madrid, G. A. (Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Bierman, G. J. (California Institute of Technology, Jet Propulsion Laboratory, Navigation Systems Section, Pasadena Calif., United States)
Date Acquired
August 9, 2013
Publication Date
January 1, 1977
Subject Category
Space Communications, Spacecraft Communications, Command And Tracking