Process noise models There are several ways to handle these types of variations Often, new observables can be formed that eliminate the random parameter(eg, clocks in GPS can be eliminated by differencing data) A parametric model can be developed and the parameters of the model estimated(eg. piece-wise linear functions can be used to represent the variations in the atmospheric delays) In some cases, the variations of the parameters are slow enough that over certain intervals of time, they can be considered constant or linear functions of time(eg, EOP are estimated daily In some case, variations are fast enough that the process can be treated as additional noise 03/1802 12.540Lec1203/18/02 12.540 Lec 12 10 Process noise models • There are several ways to handle these types of variations: – Often, new observables can be formed that eliminate the random parameter (eg., clocks in GPS can be eliminated by differencing data) – A parametric model can be developed and the parameters of the model estimated (eg., piece-wis e linear functions can be used to represent the variations in the atmospheric delays ) – In some cases, the variations of the parameters are slow enough that over certain intervals of time, they can be considered constant or linear functions of time (eg., EOP are estimated daily) – In some case, variations are fast enough that the process can be treated as additional nois e