Final Presentation

Colin Eaton

Graduate Co-op, Code 595

Mentor: Mark Woodard

August 25, 2010

ARTEMIS MISSION SUPPORT

1

OVERVIEW

• ARTEMIS

• Brief mission summary

• Related projects

• P2 z-oscillations

• P2 L1 stationkeeping analysis in STK

• STK-COM automation

• P2 L1 ODTK simulator / Tracking schedules

• Maneuver calibrations

• GMAT testing

• Testing methodology

• MATLAB scripts/functions

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3

ARTEMIS

ARTEMIS MISSION

• Extension of the THEMIS mission, and a collaboration with UCB and JPL

• THEMIS B = ARTEMIS P1 , THEMIS C = ARTEMIS P2

• First mission to navigate to and perform stationkeeping operations around the Earth-Moon

L1 and L2 libration points

• Satellites transfer from highly-elliptical lunar orbits Lissajous Libration orbits Low

lunar orbits

• NMDB is responsible for much of the maneuver planning and calibration, with additional

emphasis on Lissajous stationkeeping operations

4

THE P2 L1 Z-COMPONENT DILEMMA

• Targeted P2 Lissajous trajectories yielded uncontrolled RLP z-component oscillations

prior to exit

• Conditions must be controlled in order to capture into lunar orbit

5

km


• Performed Fourier analysis to derive periodicity

• Long-term Period: ~9 months

• Attributed to the equations of motion for the CR3BP

6

km

days

ampl

itude

frequency


• Methods for controlling z-oscillations:

• DV prior to Lissajous insertion

• Required too large of a DV to make

significant alteration

• DV at inflection point

• Requires only ~1m/s down burn to

stabilize

• Maneuver at set frequency

• Box method

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P2 L1 STATIONKEEPING ANALYSIS

8x

P2 L1 STATIONKEEPING ANALYSIS

• Stationkeeping methods

• DV at each x-axis crossing (a.k.a. half-rev)

• DV at every other x-axis crossing (a.k.a. full-rev)

• No significant advantage over half-rev

• Half-rev for first 2-3 maneuvers, then full-rev

• Methods for DC convergence

• Vx=0

• Gate method

• “Give it a push” method

• Wrote ARTEMIS procedures section

outlining the primary methodology in STK

9x

STK-COM AUTOMATION

• Had the desire to make the stationkeeping operations much more convenient

• Most tasks were very repetitive

• Became familiarized with STK-COM as per Kevin Berry’s suggestion and learned

the basics with Cassie

• Object-oriented programming using MATLAB to control the STK GUI

• Wrote various scripts to automate common tasks that did not require “eyeballing”

• Still exploring ways to add some autonomy to allow less user input

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for i=1:3

click.m

end{

STK-COM AUTOMATION

• MATLAB scripts

• COMbase.m

• Connects to STK and stores the threads to common objects from the stkp setup (e.g.

MCS segments, DV’s, etc.) into MATLAB variables for easier manipulation

• COMTest_better.m

• Loops through all (or specific) target sequences to change settings such as:

profile action, zeroing out DV’s, applying profiles, DC step/pert sizes, etc.

• COMTest_fordave2.m

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Read in GMAT ∆v

Store as STK ∆v

Correct ∆v

STOPAdd targ.

∆vTarg.

param’sApply ∆v

Differential CorrectorPass

Fail

Radial-only ∆v

ODTK SIMULATOR / TRACKING SCHEDULES

• Wanted to perform trade study on tracking schedules for P2 at L1 using the following tracking systems:

• DSN (Madrid, Canberra, Goldstone)

• BGS (UC Berkeley)

• MILA (GSFC/KSC)

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• Purpose of the study was to

determine how much tracking is

adequate to yield converged

solutions of the orbit state

• Used ODTK (not to be confused

with ODTBX) to simulate

tracking data from the stations

based on custom tracking

intervals


• First studied mathematics behind the software and spent time with Mark to

find the “things to look for”

• Ran results through the sequential filter and fixed-interval smoother to

check convergence

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• The first step was to create the customized tracking schedules for each station

• Requirements provided:

• DSN: Alternate between N/S hemisphere, every other day for 3.5 hours/pass

• BGS: Two 45-min passes every day

• MILA: One 1-hour pass every day

• Created random schedules by hand at first

• Decided to write MATLAB scripts to make my job easier

• checkSched.m – compares a newly generated schedule to be integrated with an existing schedule (e.g. adding my BGS passes to the DSN schedule I had to check for overlaps)

• makeSched.m – creates a new tracking schedule of multiple stations with various types of parameters and requirements

• Currently includes my DSN passes, hope to add BGS and MILA in future

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• Ran into various software-related and physical problems (even some that Jonathan

couldn’t fix!!!)

• Filter/smoother position/velocity uncertainties and measurement biases

sporadically explode from case to case

• SRP and transponder bias don’t have realistic physical ties when iterations

converge

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• ODTK often doesn’t work properly on my

computer unless Jonathan touches the

keys

• Unable to make any decisive conclusions thus

far in the simulator analysis

• Also attempted P1 L2 simulation, but ran into

same problems

MANEUVER CALIBRATION

• For the majority of the summer, P1 and P2 were performing deep space and trajectory

correction maneuvers

• P1: TCM-6, TCM-7

• P2: DSM-1, DSM-2, TCM-2, TCM-3

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• Provided parallel analysis to Dave’s GMAT

calibrations using ODTK

• Most iterations correlated quite well

• Also performed pre-maneuver analysis

• Biased the nominal DV’s to account for

maneuver execution error

• Wrote ARTEMIS procedures document for

calibration process

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GMAT

GMAT TESTING

• Asked to help participate in GMAT testing with Steve and Joel for

December release of the software

• Responsible for various aspects of the “Save” command

• Finding all unique GUI configurations

• Creating the script and output files necessary for comparison

• Developing the comparator

• Running cases through the comparator

• Had fun learning how to utilize regexp()

• i.e. translating Joel’s native language

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GMAT TESTING

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GMAT

Saved data file

Comparator

Result (P/F) Report

.script / .truth file

.tc file

.truth file

• Testing Methodology:

Test System

GMAT TESTING

• MATLAB scripts/functions:

• makeSave.m

• Runs entire comparator process requiring only the object class and setting extension

• @SaveComparator\Compare.m

• Extracts saved object properties from .script/.truth file

• Much regexp’ing…

• Searches for same data in saved/.data file

• Checks “Create” and property lines

• Yields pass/fail result

• Must match property name and property value exactly to pass

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ACKNOWLEDGEMENTS

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• Mark Woodard

• Dave Folta

• Jonathan Lowe

• Steve Hughes

• Joel Parker

• Kevin Berry

• Conrad Schiff

• Cassie Alberding (and the LCP)

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Thanks for your time!

QUESTIONS?

Final Presentation

Technology

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