ARTSN: PROTOTYPE FOR AN AUTOMATED REAL-TIME

AIAA-98-4185 ARTSN: PROTOTYPE FOR AN AUTOMATED REAL-TIME SPACECRAFT NAVIGATION SYSTEM L. A. Cangahuala, T. R. Drain, and P. D. Burkhart Navigation and Flight Mechanics Section, Jet Propulsion Laboratory California Institute of Technology,4800 Oak Grove Drive, Pasadena, CA91 109-8099

Abstract

Lntroduction

The &&mated Beal-zime Spacecmji Havigation system(ARTSN) is a prototype of a newclass of sojbvare for automated spacecraji navigation ad monitoring. This prototype will lead to improvements intheefficiency ofthe navigationanalysisprocess, enabling simultaneous supportof additional spacecmjl by a single analyst. Additionally, faster orbit solution generation, relative tomanual systems, reducesthe tumaroundtime betweencriticalevents and the required response, allowing new modes of operation with This is increased reliability and reduced costs. especially important during critical events such as the launch phase, aerobraking,maneuvermonitoring, ad approach. The current ARTSN prototype has four components: a datapre-processor, a shell interface, an engine, and dm displays. date, To there have been end-to-end demonstrationsofARTSNcapabilitiesacrossseveral deep space missions. In mid-1997, ARTSN was tested processing mw data from theend of Mars P a t h w r interplanetarycruise,displaying post-fit residuals ad updated Marsencounter estimates. ARTSNdisplays were also used by the Mars Global Surveyor navigation team to observe and make a ‘quick-look’ assessmentof theMars Orbit Insertion (MOI) maneuver. In early 1998, theNearEarthAsteroidRendezvous (NEAR) navigationteam usedtheARTSN pre-processor to assess the execution ofseveral spacecrafr maneuvers.

ARTSN is a prototype of a datadrivennavigation software system which autonomously processes data for orbit determination. radiometric tracking ARTSN validates andcorrectsobservables received via a network connection or file; the receipt of these observablestriggers (1) the integrationof spacecraft state vectors and dynamic partial derivatives needed to and partial (2) calculate the computed observable to relevant derivativesoftheobservablewithrespect (3) estimatesof parameters.ARTSNthencomputes and (4) parameters along with their uncertainties mappingsofthe spacecraft states and uncertainties to other epochs. In this section overviews are given of the motivationfor this system,itsdevelopmenthistory, and some of its characteristics. The appendix includes a listing of present ARTSN capabilities.

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Motlvatlos Historically, all interplanetary missions have made use of ground-based radio metric data, such as Doppler and range.Additionally,somemissionshave made use of opticalimages of targetbodiesagainst a knownstar field, telemetered to theEarth for processing, to provide targetrelative positioninformation.Withallofthese data types, theinformation is electronicallytransferred data is toagroundoperations facility, where the bufferedand stored until processed, the latency between observation time and processing time may be from as little as 10 minutesto as long as afewmonths (dependingontheneeds of the mission), with12-24 hours being typical. Newly received datais merged with already analyzeddata and the entire data setis processed via a batch-sequential least squares estimator. process, this In the identification and correction or deletion of invalid dataas well as the operation of the software is performed by an analyst operating at a workstation console. The process of fitting the data requires the use of multiple software links and the manual examination of pre-fit residuals to determine which points should be fit and which points should be deletedfromthe solution. Aftergenerating thebestestimate of thespacecrafttrajectorybasedon

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theinputmodels,theanalystmustdeterminethe and appropriate set of output coordinate frames mappings that are desired to view the solution and use thesoftware to generatepost-fitresiduals.Typically this process requires approximately one hour of additional processing time after the data is received by the operations analyst. When itis necessary to evaluate multiple models, as is the normal procedure, multiple analysts must work in parallel or additional processing time is required.

navigation softwareset, which will be closely allied to thearchitecturefromtheARTSNeffort. Inaddition, the data pre-processor has evolved beyond the prototype state, and isbeing d e l i v d to flight projectsinthe summer of 1998. Characteristics From the lessons learned in the development effort came the following characteristics of the ARTSN design: The (historically) separate modulesare integrated into asingle package.Merging the links that provide trajectory propagation, station location computation, and state and measurement modeling, filtering, covariance mapping facilitates real-time capability.

While recent missions have begun to institute greater automationofportions of theorbitdetermination use process, the natureof the automation focuses on the of scripts and automated routines which use the legacy software insteadof the development of a robust system Modern software techniques were used to implement intended for automated use. Although such automated the existing algorithms. The resulting highly Earth orbiting systems have been developed for be modified easily. modular components can thus missions, they have not previously existed for Interfaces in the packages were arranged to facilitate interplanetary missions. With such a system,one could the system’s use in a distributed environment. automate the generation of predicted spacecraft positions for ground stations, and provide an operational tool for Except for someof the graphical user interfaces(GUIs) fastturn-aroundapplications. This system is making and some of the low level file readers, all of the code tasks groundautomationofinterplanetarynavigation was written in C.” The ARTSN prototype only requires more routine, andis serving as a ‘stepping stone’ to an an AmericanNational Standards Institute (ANSI) C on-board interplanetary navigation system. compiler in order to run on a particular platform. ’Ihe ARTSN code is not purely object oriented. However, Development in the code is arranged into objects, and these objects The conceptual design of ARTSN was begun in 1994 spirit do fit the ‘black box’ metaphor usually given to by Pollmeier and Masters’atthe Jet Propulsion object oriented programming; that is, the object Laboratory (JPL). The resulting high-level design, contents are encapsulated so that a programmer using =fend to as RTAF(Real-TimeAutomatedFilter), the object wouldn’t have to know the contents of the brought out several key lessons: object itself. Modularize system thearchitecture whenever The design of the ARTSN system allows several new possible. modes of operation to be performed that have previously & controluserinterfaces Separatethedataoutput from the primary analysis system.

been unavailable to the interplanetary navigator:

J&& Dnven In the currentJPL operations navigation software suite, the analyst acts as the ‘measurement manager’; that is, Streamline the process for addition of new force and or no computed measurements, pre-fit residuals, observable models. measurement partials are calculated until the user runs From RTAF, the next step was to build the ARTSN the appropriate software link. The analyst must decide prototype, short-term with the objective of howmuch data is senttothelinkatthetime of demonstrating automated radiometric data processing andexecution.When the link is executed, the number of orbit determination for interplanetary cruise. The points processed is knownand fixed; the arrivalof new authorsperformedthedevelopmentand testing of the data doesnottriggeranynewactivity. In ARTSN, prototype,investingapproximately 2.5 work-years in there is a simple measurement manager included in the the effort. Automated orbit determination with ARTSN was first demonstrated in late June 1997; based on the * This was achoicedriven by theprogramming success of thesedemonstrations,a new effort was backgrounds of the developers, not by any performance initiatedin late 1997 to create a‘nextgeneration’ or compatibility criteria. 2 Use commercial software when possible.

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engine; with this manager, the system is drivenbythe arrival of data. No user interaction is needed to process newdata;alltherelevantcalculations are performed upon the arrivalof each observable. Filtering Options In the current JPL operations navigation software suite, the analyst performs trajectory estimation using a batch data sets are iteratedon sequentialfilter.Complete usingareferencetrajectoryinorder to converge to the best solution. Using this system, it is very difficult (if not impossible) to process new data in real time. While the ARTSN system can also operate in this mode, its realstrength is theabilitytoprocess data using an Extended Kalman Filter (Em. This approachupdates themodels and thetrajectory as each data point is received.Thesolutionatanygiventime is thebest estimate of thetrajectory (and can be viewedin real time). on Dgmand TheARTSN“measurementmodeling”module,upon data point, requests state and partial receiptofa information about aspecific measurement type and time fromthe“participant”and“propagator”modules(that is, the portions of the system that deals with trajectory and dynamic partial information). Likewise, the and “parameter predictor” task requests estimate covariance information from the same modules at specific mapping times. ARTSN can be configured to any pieces of information after specifiedamounts of timehaveelapsedor a certainnumber of data points havebeenprocessed. This allows realtimedisplay to be automatically updated, giving an analyst rapid access to a wide varietyof information.

Data Pre-Rocesso~ The data pre-processor, xef& to as ARDVARC (Automated Radio metric Data Visualization and Realtime Correction), creates measurement mods from the raw DSN datestream.ARDVARChasfourmajor capabilities: (1) Validation and correction of radio metrictracking data, (2) Export of validated observables to real-time and offline orbit determination software,

(3) Real-timemonitoring and analysis of radio metric data residuals, (4) Real-time monitoring of the tracking of a spacecsaft across all DSN stations(e.g. a history of what stations have been tracking the spacecraft of interest). Theinputs to theARDVARCprocessincludestation time information between the locations and light spamaaftandgroundstations.ARDVARC is a datadriven pre-processor; upon receiptof a series of Doppler phase counts, ARDVARC attempts to build a Doppler this candidateobservablepassa observable.Should seriesofconsistencychecks,ARDVARC,usingselfgenerated view period information, then creates list a of candidate uplink stations, and creates “hypothetical residuals” and residual rates to determine which station mostlikelytransmittedthesignal(noinformation abouttheidentity of thetransmitter is encodedinthe selected, the signal). Once a transmitter has been configuration data are examined and c m t e d , resulting in a logically consistent series of data points.

To illustratethecomparisonofhypotheses,Figure2 shows“hypotheticalresiduals”builtduringatracking DescriDtion handover of MarsGlobalSurveyor(MGS)coverage from the Deep Space Network station (DSS) 15 (at the Figure 1 shows the ARTSN components, as well as the Goldstone complex) to DSS 45 (at the Canbema data flow throughout. The currentARTSNprototype complex). The residuals on the relatively straight hasfourtypes of components:adatapre-processor,a any portion correspond to thecorrecthypothesisat shell interface, an engine, and data displays. The given time (The absolute magnitude of the true MGS interactionbetweenthecomponents is handledwith the pre-fitresiduals(-tens of H z ) is duetoerrorsin machine portable data structuresof XDR (external Data predicted trajectory due to aerobraking). Initially, w t e Representation) encoded binary packets through TCPDP way and three-way Doppler is being received at both network connections. stations 15 and 45. DSS 15 is the transmitting station. ARTSN receives tracking data (which contains Doppler Shortly after 01:35:00 (Earth receivetime),DSS15 and range measurements) from the Deep Space Network stops receiving data. At approximately 01:52:00, (one (DSN) stations in the TRK-2-15A format, a bit-packed round-triplighttimelater)theDSS 45“hypothesis” This raw formattransmittedoveraUDPconnection. the transmitting becomes correct; DSS 45 is now tracking data is unpacked, corrected, and reformatted in station.Byinspectionit is relativelyeasytoidentify real time by the ARTSN pre-processor. the “correct” transmitter in this figure; the ARDVARC and transmitter selection algorithm uses residuals 3

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residualrates to performasimilaroperation time..

in real-

processor. In terms of Figure 2, the ARTSN shell and engine boxes are now combined into a single process.

Eneine

Theresultingvalidateddatapointscanthenbeoutput via XDR packets (to the ARTSN engine) or to afile (in File (ODF),foruseby the this case anOrbitData operational DPTRAJ/ODP software suite). The ARDVARC pre-processor is anexample of a system and compatible with existing operational software prototypes of future interplanetary navigation software.

The ARTSN engine is the primary computation module. Modules in the engine perform trajectory integration, measurement observable computations, and parameter mapping. filtering, event detection, art performed by the Overall,themajortasksthat ARTSNobjects am depicted inFigure 4. Note that these are major tasks, and not definitions of the objects themselves; that wouldbe beyond the scope intended for this paper.

ARDVARCcanbe aperated throughagraphical user interface (CUI) called XARDVARC; fromthis interface, as analysts can control many inputs in real time, such

Theabilityoftheengineto be remotely commanded allows the input and output processesto be modified for specific projects and users without the need to modify (and re-test) the engine. The majority of the algorithms implementedintotheARTSNenginewereoriginally derived for the existing navigation softwam set. 2*3 The modeling configuration and general data inputs quid by the engineare handled through namelistfiles.

Doppler observable count time Times to create up-to-theminute ODFs Thresholds for acceptinghejecting residual values XARDVARChasgraphicaldisplaysfor: (1) real-time results of the ongoing vafidatiodcorrection process, (2) atextsummary of theproblemscorrected, (3) a userinteractive (scaleable, resizeable, with labeling capability) plot of all Doppler and range residuals, (4) an algorithmformakinga‘quick-look‘assessmentof the line-of-sight componentof a maneuver (without any a priori information about the event), and (5) a station coveragemonitor based onthevalidated data builtby ARDVARC.

Interior to the ARTSN software, the primary means of bookkeeping and storingmodel data is through the concept participant. aof The term ‘participant’ encompassesall‘thingsofinterest’inanynavigation scenario. Participants include tracking stations, spacecraft (probes), and natural bodies (including Shell Interface and comets). This system is satellites, asteroids, The ARTSN shell (ash) is command-line a style of the numberof designed to easily allow for the scaling interactive user interface that translates namelist inputs all existing newbodies,stations,etc.knowingthat or into engine commands (for a locally executing engine physical considerations (forces, rotations, etc.) m one running on a remote machine). The shell serves as available to these new participants. One of the primary the primary means for controlling data sources and the attributes of a participant is the concept of adynamic execution of the ARTSN engine. The shell follows a state.Eachparticipantknows it’s ownstate(atany simple command line style parsing algorithm with ontime)withrespecttoanotherparticipant (it’s parent). 3 linehelpforeachoftheshellcommands.Figure tree” canbe created in Usingthisapproacha“state depictsatypicalARTSN session (operatinginbatch which relative states between any two participants can UNM workstation, with sequential mode) on a be easily computedbywalkingthestate tree. The explanations ofthe shell commands used. actualstateoneach leg of the tree is computedbya The ARTSN shell has two primary configurations, both participant’s propagator. of which can be used in real-time and off-line capacities. ProDanatorS ‘network’ One configuration, r e f d to as the To compute the relative states for any two participants, configuration, is used whentheengine is runningon and their states must be “propagated” to the correct time and output activities coordinateframe.Each oneprocessor,withtheinput leg of thestate tree canbe possibly on other processors. In this case, the ARTSN propagatedindependentlybydifferentalgorithms. This remoteshell is used tocommunicatewiththeengine approachmakes it easytomixdifferentmethodsof using remote procedurecalls over a TCPAP connection. computationfromsimpleconicsuptohighfidelity The second configuration, referred as to the ‘stand-alone’ numericalintegration.ARTSNhasthreeclassesof configuration,hasthesystemrunningonasingle state propagators: 4 American Instituteof Aeronautics and Astronautics

Earth station location Ephemeris. The position and velocityof natural bodies are propagatedusingalookupmethodfrom Observable and partial generation precomputed files. Theseephemeris file names and Batch filtering locations are specified through the namelist inputs. In general,a reader can be set up to get position a d State and covariance mapping velocity data from a file, conic approximation, or any Aftertheinitialcheckout,therehave been several other formula or datafile for any participant. opportunitiestoworkwithflightoperationsteams to Vector Rotation. Rotational propagation is the These demonstrate the capabilities ARTSN. of generalized form of what is traditionallythemethod collaborationshavebeenvaluable, as it significantly used totransformtrackingstationlocationsfrom reduced theeffort needed to gatheralltherelevant bodyfixed frames to inertial frames. The more modelinginputs, and thenavigationanalysts on e& general case allows not only for rotated stations, but mission have pvided valuablefeedback. Sinceno as also forarotatedspacerraftonanybody,such single particular mission captures all of the challenges landers. presented tonavigationanalysts, it wasimportant to interact with different projects whenever possible. Integration. Numericallyintegratedparticipants are traditionally spacecraft. The current integration hlmmalk propagator is Runge-Kutta-Nystrom a (R-K-N) After the initial validation, ARTSNs first 'real world' seventh-order algorithm with eighthorder state tests was performed with Mars Pathfinder tracking data. control. This integratorcan be used infixed-step The objective was to produce current state and epoch mode,wheretheintegrationstep size is specified state solutions over a 76 day data arc. These solutions initially andremainsconstant,orinvariablestep werethen used tomakeencounterestimates;in both mode,where an errortolerance is used to determine modes the ARTSN estimate agreed with that generated the maximum step size that meets the specified erm bythePathfindernavigationteamtowithin less than limit. Supported force models are listed in the halfof the pathfinderestimateuncertainty,which is appendix. and maneuver suitableforstationpredictgeneration DUt Data 5 shows thecomparison of B-planet design.Figure The displays connected to the ARTSN engine for output estimates for a setof ARTSN current state solutions to the solution prepared by the Mars Pathfinder navigation graphical applications; any purposes are LabView team. be used to package with a TCP/IP network interface can create anARTSNreal-time display. Byusingremote A demonstration was also performed using 'an unedited procedure calls across the network, display a can recording of a DSN broadcastof the final two weeks of configure the engine to send the correct data stream back Mars Pathfiider before entry into the Martian toitself without the user interacting directly withthe atmosphere. This time span included the final trajectory be engine. Frontand back-end displays can correctionmaneuver,TCM-4, and apatch of data implementedonrelativelyinexpensivedesktopPCs corrupted by the improper application of a leap second while the engine runs on a workstation. correction at the DSN. As the data was processed, the solutionevolved,accountingforthemaneuver and LabViewprovidesagraphicaldataflowlanguagewith rejecting most of the corrupted data. 5 shows whichtocreatedisplayapplications4;Figure as it was the Labview-based Doppler observable display used duringtheMarsGlobalSurveyorMarsorbit TheMarsGlobalSurveyor (MGS) navigation team insertion. demonstrated real-time navigation using ARTSN during the Mars Orbit Insertion (MOI) on September11,1997, and during the aerobraking phaseof the mission to date. A validation of the ARTSN software was performed by ARTSN read radio metric Doppler data in real time and operations software comparison to the existing computed measurements based on an ARTSN-generated (DPTRAJ/ODP). The agreementbetweenthe software nominal trajectory. Streams of observable and residual suites wasatthenumericalprecision level. Specific values were piped to several displays in real-time, both validation checks included:

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Trajectory and transition matrix integration The asymptotic approach plane at Mars.

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to the public (see Figure 6 ) and the navigation analysts themselves.

autonomousorbitdeterminationfora long, quiet cruise phase.

The MGS navigation team continued to use the and pre-processor monitor to ARTSN displays aerobraking-related events,such as periapsis-lowering maneuvers, and tracking before and after each periapsis shifts during the pass. The line-of-sight Doppler maneuvers were reported back to the project as a ‘quicklook’ assessment of the event, and the effective Doppler shift from each aerobraking pass was also monitored as tracking resumed after each pass.

The vision forARTSNforthefuture will be realized through the development of the next generation navigation software system.Thevisionincludesa significantexpansionof its capabilities,especiallyin higher level optimization and regulating tasks.

The ARTSN preprocessor (ARDVARC) is of special use to theMGSnavigationteam.Theresumptionof aero-braking in the Fall of 1998 will require the rapid turn around ofnavigationsolutions as themapping u c e d . ARDVARC’s ability to orbital period is d correct and create tracking data files (for use with the currentsoftware)inreal-timecansignificantly duce the latency between the timethe data is received and the time the analyst can begin working.

NEAR InJanuary1998thereal-timedisplay of ARDVARC was used to observe a small maneuver performed bythe NEAR spacecraft. Output from the ARDVARC graphicaldisplaywas used bytheNEARnavigation team at JPL to notify the project that the maneuver had beenexecuted. In order tomore closely observethe maneuver, the Doppler count time was changed“on-the the fly” from 10 secondsto 1 secondshortlybefore maneuver. Once the‘quick look‘assessment of the maneuverwascomplete,thecounttimewaschanged back to 10 seconds, in order to lower the volumeof data to be post-processed. This ability to change the processing configuration real-time in has proven invaluable.

spacecraft ina

&owlThe ARTSN task objective was to automate navigation functions using algorithms already the JPL in DPTRAJ/ODP software suite; acknowledgmentis given to those allwho participated in historical its development. Special thanks go to Ted Moyer and Rick Sunseri for their constructive advice and availability for Mars Global discussions. Thanks also go to the Surveyor, Mars Pathfinder, Galileo, and NEAR navigation teams for their cooperation during the validation phase of the ARTSN and ARDVARC was prototypes. The work descxibed in this guide carried out by the Jet Propulsion Laboratory, California under contract with the Institute of Technology, National Aeronautics and Space Administration.

References W. C. and Pollmeier, V. M., 1 . Masters, a Prototype Real-Time “Development of Space Automated Filter for Operational Deep Navigation,” Third International Conference on Space Mission Operations and Ground Data Systems, Goddard Space Flight Center, Greenbelt, MD, 14-18 November 1994. 2. Ekelund, J. E., DPTRAJ/ODP User’s Reference Manual, Propulsion Jet Laboratory Internal Document: D-4533, Pasadena,California,15May 1988.

A month later, there was an opportunity to observe six thruster firings by the NEAR spacecraft. An annotated plot showing the results of this monitoring ( s e e Figure A-V assessments,was prepared 7) along with the seconds after the end of the data arc shown.-

3. Moyer,T. D., “MathematicalFormulation of the Double Precision Orbit Determination Program (DFQDP),” JPL Technical Report TR 32-1527, 15 May 1971. 4. Johnson,G.W.(Machover, C., editor), J a b v i e w Grap-, McGraw-Hill, Inc, 1994.

Elimams Withthesuccessfulseriesofdemonstrationsofhighhas served as a fidelityorbitdetermination,ARTSN ‘stepping stone’ between the current paradigm of interplanetarynavigation and a new paradigm with an emphasisonreliableautomatedprocesses.There are scenarioswhereanautonomousornearly-autonomous presence would be of benefit, such as spacecl-aft trajectorypredictionsforgroundtrackingstations or

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e varvw Cartesian, cylindrical, spherical, classical, B-plane types Body/Space, “Ne, Equator,Orbital, EpocWOf Date frames User defined coordinate frames (axes pointing at another participant, an inertial direction, or the velocity vector) Systems are defined and labeled, then referenced for use by all input and output routines Defined systemcan be configured to vary with time

ADDendix ...

BBTSN ComDutational CaDablhhes to Rate Mod& Spacecraft and landers Tracking stations Natural bodies (planets, satellites, and small bodies)

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Runge-Kutta-Nystrom (R-K-N) seventh-order integration algorithm with eighth-order state control Body fixed rotation (for ground stations and landers) NAVIO planetary ephemeris NAVIO satellite ephemeris SPICE ephemeris

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Flat plate, cylindrical and spherical component types Time-varying components Orientation in any coordinate system (including timevarying coordinate systems)

Eilter UD factorized, scaled Kalman filter Random walk, constant, and exponentially correlated random variable (1st order Gauss-Markov) process noise models Multiple batch mode (time bounded or number of measurement bounded batches) Current state Extended Kalman mode

EQK&hw Newtonian and relativistic gravity and arbitrarily sized oblate gravity fields for any body Solar radiation pressure (using spacecraft component model) Finite and impulsive motor bums Arbitrary time-varying polynomial accelerations Atmospheric Drag (exponential density)

0

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Differenced range Doppler 1, 2, and 3-way Range 2 and 3-way Wet and dry Neil1 troposphere signal delays Participant delays Participant specific measurement biases Data editing (by checks for min. elevation angle, maximum allowable pre-fit residual)

Spacecraft position and velocity Stations locations (Cartesian or cylindrical) Finite bum force, right ascension and declination Impulsive burns Solar pressure scale factor Solar pressure component scale factor Unmodeled accelerations Measurement biases (for eachDarticiDant)

Pole motion Plate motion Ocean,solid, and pole tides High precision time transformations

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Mars Global Surveyor

D S N Handover Hypothetical Transmitter Residuals D S S 15 ( G o l d s t o n e ) t o D S S 45 (Canberra)

16':00

Figure 2. Mars Global Surveyor Doppler ResidualsBased on Two Different Tmsmitter Hypotheses albeemenlo: -: a r t s n

startof A

d 4 .

AutomatedReal-Time Spacecraft Navigation System Section 312 Navigation & F l i g h t Mechanics Version 2 . 0

R ~ N session

namelist load: Parses

files

December 1997

msr: Establishes mode for processing incoming XDRrecords ash:load./inputs/eop.nml

ash: msr f i l t e r

ash: m s r comp

4 ash: Q Q u i t t i n g. . . albeQmen1o:-:

End of ARTSN session

Figure 3. ARTSN Shell Session

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Encapsulate hardware Handles how measurements are specific data into general measurement incorporated in the system software obiect (batch, real-time, etc)

Handles storagelretrieval and identification of models (atmosphere,

Parameter Prediier

.

L

FILTER

PROPAGATOR Generates dynamic state and state partials at any

MAPPER

Given residual and Generate value residual partials, and uncertainty of a parameter computes the uncertainty and state at any epoch or event update. Also computes uncertainties at a requested epoch

[ Dynamics Modeling

Figure 4. ARTSN Task Breakdown Diagram

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Orbit Determination Solutions: B-Plane Locations Mapping Frame: Mars-Centered Mars Mean Equator of 2000 -1 840

-1820

h

8 G p1

-1 800

-1780 -1760

-1740 -4580

-4560

-4540

-4520

-4500 BOT 0-1

-4480

-4460

-4440

-4420

Figure 5. Comparison of ARTSN Current-State Mapped B-Plane Estimatesvs. Solution Prepared byMars Pathfinder Navigation Team Note: TheMars Pathfinder (MPF) B-Planeellipse contains orbit determination(OD) uncertainty as well as consider parameters; the ARTSNellipses contain onlyOD uncertainties.

Planetary targeting is usually expressed in termsof the B-plane, a plane passing through the center of a target planet and perpendicular to the incoming approach hyperbola asymptoteof a spacecraft. ‘‘B*T’is the intersection of the B plane with the ecliptic and “BOK’is a ‘mthward‘ pointing vector in the B-plane that is perpendicular to BOTand making a right handed system R, S, T, where S is the incoming asymptote.

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Figure 6. ARTSN Display of Doppler Observables Shown on the JPLlMGS Home Page During MOI - Predicted l-way Doppler Obs.for DSS 15 for a nominalMOI BottomTrace - Predictionsfor DSS 45, &aw ProcessedDopplerObservables

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XARDVARC Real-Timc R-idualr

"

I...!.......!.......!....... 11-FEB-1998 l3:33:20.00

11-FEB-1998

ll-FEB-1998

! . . . . . . . 11-FED-1998 ].....I

11-FEB-1998

2-u*y

1440 m.m u:l3:2oM) 1s:*:4o.m Earth Receive Time (UTC) Figure 7. NEAR Doppler Residuals on 11-FEB-1998(XARDVARC display, ARDVARC Delta-Freq. estimates) 14:06:40.00

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