GLOBAL ATMOSPHERIC DENSITY ESTIMATION USING A SEQUENTIAL FILTER/SMOOTHER

摘要

Sequential estimation algorithms are applied to the problem of global atmosphericdensity estimation. An optimal sequential filter is combined with avariable lag smoother to investigate the estimation of corrections to intermediarytemperature parameters in the Jacchia 1970 atmospheric density model. Ofspecific interest are the time lag required to provide the most accurate definitiveestimates of temperature corrections, and the observability and correlationassociated with several parameterizations of the temperature corrections.