*2.4. An Overview of the Newcomb Program Structure*

The top level process structure of Newcomb is shown in Figure 8. Basic

operation is as follows.

The observations module is responsible for reading input astrometric ob-

servations and reducing ("massaging") them as necessary. The observa-

tions will be of various types (Figure 5), taken at various observing loca-

tions (Figure 11), including spacecraft. The reduction process corrects for

various instrumental and other effects (e.g. from the atmosphere) that are

specific to a particular set of observations.

The integration module is responsible for numerically integrating a so-

phisticated dynamical model of the solar system -- including general rela-

tivistic terms, a detailed Earth-Moon system, planetary spin vectors includ-

ing precession and nutation, and an unlimited number of asteroids -- to

produce an ephemeris.

The model ephemeris is then compared with the observations in the O-C

section of the parameter adjustment module to produce a set of residuals.

The parameter estimator uses the partial derivatives of the model equations

with respect to the model pa-

rameters (including initial

conditions) to solve the asso-

ciated nonlinear least squares

problem for the most prob-

able set of model parameter

values that minimizes the

O-C residuals.

The adjusted model pa-

rameters are then fed back

into both the ephemeris gen-

erator and the observation

transformation methods. The

data are rereduced as neces-

sary, and a new ephemeris is

generated by the integration

module, using the updated pa-

rameter values. These are

again combined to produce a

MURISON: MODELING PLANETARY MOTIONS

13 of 20

Figure 8 -- Major program processes.

iteration

loop start

massage

observations

integrate eqs.

of motion

form O-C

residuals

parameter

estimator

O-C

eval

iteration

loop end

observations

reduced

observations

ephemeris

parameters

correlation

matrix

observations module

parameter

adjustment

module

integration module

physical

model

observation

models

calculate

observables

data

data flow

process

parameter feedback

process flow