NASA Technical Reports Server (NTRS) 20030005452: Aerocapture Guidance Algorithm Comparison Campaign

10 Pages·0.71 MB·English

by  NASA Technical Reports Server (NTRS)

AIAA-2002-4822
AEROCAPTURE GUIDANCE ALGORITHM COMPARISON CAMPAIGN
Stdphane ROUSSEAU*, Etienne PEROT;
Centre National d'Etudes Spatiales
Toulouse, France
Claude Graves, James P. Masciarelli*
NASA Johnson Space Center
Houston, TX
And
Eric Queen*
NASA Langley Center
Hampton, VI
Abstract Nomenclature
The aerocapture is a promising technique for the future AFE Aeroassist Flight Experiment
human interplanetary missions. The Mars Sample Re- APC Analytic Predictor Corrector
turn was initially based on an insertion by aerocapture.
CNE S Centre National d'Etudes Spatiales
A CNES orbiter Mars Premier was developed to dem-
onstrate this concept. Mainly due to budget constraints, EC Energy Controller
the aerocapture was cancelled for the French orbiter. A
lot of studies were achieved during the three last years EMCD European Martian Climate Database
to develop and test different guidance algorithms (APC, Hap Apoapsis Altitude
EC, TPC, NPC). This work was shared between CNES
and NASA, with a fruitful joint working group. To fin- JSC Johnson Space Center
ish this study an evaluation campaign has been per- Mars GRAM Mars Global Reference Atmosphere
formed to test the different algorithms. The objective Model
was to assess the robustness, accuracy, capability to
limit the load, and the complexity of each algorithm. A MSRO Mars Sample Return Orbiter
simulation campaign has been specified and performed
NASA National Aeronautics and Space
by CNES, with a similar activity on the NASA side to Administration
confirm the CNES results. This evaluation has demon-
strated that the numerical guidance principal is not NPC Numerical predictor Corrector
competitive compared to the analytical concepts. All TPC Terminal Point Controller
the other algorithms are well adapted to guaranty the
success of the aerocapture. The TPC appears to be the Introduction
more robust, the APC the more accurate, and the EC
appears to be a good compromise. The planetary low coast insertion is an important chal-
lenge of the current and future interplanetary missions.
*Engineer, Mission Analysis Department
; Engineer, COFRAMI, Toulouse, France
*Engineer, Aeroscience and Flight Mechanics Division, Member AIAA
Copyright © 2002 by CNES. Published by the American Insitute of Aeronautics and Astronautics, Inc. with permis-
sion.
1
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Theaerocaptuwreasretaineadsacompetitivceandi-
set of expected aerodynamic, atmospheric and
dateforthefutureMartianmissionMarsSampRlee-
OD dispersions
turn.ThiscollaboratiNveASA-CNEmSissionwillbe
precedebdyaFrencdhemonstraMtoArRSPREMIER, The complexity : the complexity corresponds
launcheind2007M. ainlyduetobudgeretasoMn,ARS to the on-board code complexity. It mainly
PREMIEwRillnomoreuseflaeaerocaptubruet,aclas- contains the number of operations, test, loops,
sicaclhemicianlsertion. and so on.
Inordetrodemonstrathteeaerocaptucroenceptth,e In order to define test cases, it is necessary to under-
CNEShasdevelopfeodurdifferengtuidanpcerinciples: stand what the main parameters for the aerocapture, and
the associated uncertainties are.
- theAnalyticaPlredictCororrecto(ArPC)
Aerocapture main parameters
- theNumericParledictoCrorrect(oNrPC)
- theTerminPaloinCt ontrolle(TrPC) The aerocapture is a very stringent technique, that de-
pends on several parameters. To study the aerocapture,
- theEnergCyontrolle(ErC)
it is necessary to consider either mean parameters (mis-
sion description, entry corridor), but also the excepted
Inordetroconsolidathteeaerocaptucorencepat,com-
uncertainties, till the unexpected uncertainties (stress
monNASA-CNEwSorkinggrouphasbeenformed.
cases).
Thegrouphasdemonstrattheedfeasibilitoyftheaero-
captureandthecapabilitoyfall thealgorithmtso Mission description
achievteheaerocaptuTrhee.currenptapeprresenftlsae
evaluatiocnampaigmneanttotestthedifferenatlgo- The aerocapture consists in an atmospheric pass to slow
rithmsinordetroselectthebestonefortheMartian the vehicle, and to reach a specific orbit. It corresponds
missions. to a given AV realized by the aerodynamic force.
Therefore, the main parameters are :
Theobjectivisetoevaluattheealgorithmosndifferent
- the AV value which is fixed by the arrival ve-
topicsi,nordetrodeterminifeoneismoreadaptetod
locity and the targeted apoapsis,
theaerocaptuthreanflaeothersT.hispapeisrdivideidn
fourparts:
- the aerodynamic force which depends on flae
vehicle characteristics (aerodynamic coeffi-
- thedescriptioofnthedifferentetsctases
cients),
- thesimulatiotonols
- the atmosphere (density and wind).
- theNASA/CNEcSomparison
It was decided to test different combinations of those
- theanalysoisftheresultasndthefinalranking
parameters to evaluate the algorithms. But an exhaus-
oftheCNESalgorithms.
tive combination was not possible, so a set of potential
missions was defined to cover different combinations of
Test case description those parameters.
The objective was to evaluate four main criteria :
Infinite L/D, Hap Atmospheric
mission
- The accuracy : being given a set of expected Velocity Mass target model
aerodynamic, atmospheric and OD disper-
sions, the accuracy of the algorithm was de- 2005 cls 3.2 .25, 1400 Clear, dust
fined as the final orbit statistical maximal dis- 2200 marsgram
tance to flaetargeted orbit.
- The robustness : the robustness was defined as .25, 1400 Clear, dust
2005 opn 2.9 2200 marsgram
the capability of the algorithm to handle with
high dispersions.
.28, 1400 Clear, dust
2007 ref 2.6 2500
- The loads control : the loads corresponds to
the thermo-mechanical loads applied to the
vehicle during the aerocapture. The loads con-
.28, 4000 Clear, dust
trol was defined as the capability of the algo- 2007 low 3.2 2500
rithm to limit the loads variation, being given a
American Institute of Aeronautics and Astronautics
mission Infinite L/D, Hap AtmosphericThis theoretical corridor depends on the atmosphere
VelocityMass target model characteristics, on the ballistic coefficient SCD/m and on
the Lift-to-Drag ratio L/D of the vehicle, on the arrival
velocity and on the targeted apoapsis.
.28, 500 Cleard,ust
2007polar 2.6 2500
- the lower the Lift-to-Drag ratio, the narrower
the corridor,
Cleard,ust,
.28, 1400 dus2t,dust - the higher the arrival velocity, the larger the
2007dust 2.6 2500
5 corridor,
- the lower the targeted apoapsis altitude, the
Theatmosphhearesamajoirmpacotntheaerocapture. larger the corridor,
Therefoirteisimportatnotusealltheexistinmgodels.
- the denser the atmosphere or the higher the
Asaconsequenitcwe,asdecidetoduseboththeEuro-
ballistic coefficient, the shallower the corridor
peanAtmosphemricode(lEMCD)b,aseodnaglobal
mean FPA.
circulatiomnodewl ithtwonominaslcenario(csalled
cleaarnddust)a,ndtwoextremsecenariocosrrespond-
Figure 1 presents the sensitivity of the steep and shal-
ingtodussttormcondition(csalleddus2t,dus5t),and
low boundaries with respect to the targeted apoapsis
theMARSGRAVM3.8.
altitude considering MARS PREMIER 2007 open win-
dow arrival conditions (earliest arrival time, i.e. July
Thissetofmissionwsasconsideresudfficienetnough
19th, 2008) and a AFE-like entry vehicle with
tocovetrhedifferenctombinatioonftshemainparame-
L/D=0.274 and SCJm=5.79 10-3 m2/kg (0° trim AoA
tersT.he'05missioncsorrespotnodhigharrivavleloc-
and 2500 kg mass).
ity,withlowL/DanduseofbothMARSGRAaMnd
EMCDatmosphemricodelsT.he'07missioncsover
differenatltitudetargetinagnddifferenattmospheric
scenariowsi,thaspecifidcuststormconditiona,nda
higheLr/D.
Entry corridor
Whatever the mission is, the aerocapture is driven by
the entry conditions, this is a key parameter. The spe-
cific parameter associated to the entry condition is the
Flight Path Angle, and the range of acceptable FPA is
called entry corridor.
The theoretical aerocapture corridor is the entry FPA
range that allows the vehicle to reach the targeted
apoapsis at the atmosphere exit. Figure 1 :Theoretical corridor as a function of the tar-
geted apoapsis altitude
If the vehicle enters the atmosphere at the steep bound-
ary of the corridor, the vehicle will have to flight "full A parametric study on the entry FPA, called captured
lift-up" along the whole trajectory in order to reach the corridor, has been performed on each mission, with all
targeted apoapsis. On the contrary, if it enters the at- the algorithms to determine the corridor associated to
mosphere at the shallow boundary of the corridor, the each algorithm.
vehicle will have to flight "full lift-down" along the
Expected uncertainties
whole trajectory in order to reach the targeted apoapsis.
Inside the corridor, it is always possible to find at least
The aerocapture success depends on the knowledge of a
one bank angle law that guides the vehicle to the tar-
great amount of parameters. The more important are the
geted apoapsis. On the outside of the corridor, there is
entry conditions, the aerodynamics characteristics, the
no possibility for the vehicle to reach the targeted
atmospheric density, and the on-board navigation. To
apoapsis : the final apoapsis will be lower or higher take into account the uncertainties associated to these
than the desired value depending on which side of the
parameters, Monte Carlo simulations have been per-
corridor (steep or shallow entry trajectory) is consid-
formed with the following dispersions.
ered.
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Thruster failure stress cases
Distribution Type 3-_ or
min/max
The piloting authority is also a major contributor to the
aerocapture performance. The nominal uncertainties
Mission Uncertainty
taken into account for Monte Carlo simulations were:
Initial inertial FPA, deg Normal 0.4 - +10% on bank acceleration
Aerodynamic Uncertainty
To take into account the possible loss of one thruster or
TrimAngle ofAttack Iner, deg Uniform 2.0 more, the following variations were considered:
Axial Force CoeffIncrement Uniform - -25% and-50% on bank acceleration
10%
Processor failure stress cases
NormalForce CoeffIncrement Correlated
The aerocapture phase is achieved in a fully autono-
Atmospheric Uncertainty
mous way. Once this sequence has been initiated, there
InitialSeed Value Uniform is no possibility to abort it. That is the reason why the
two on-board processors are in hot or warm redun-
dancy. In case of failure, the time required to swap from
Control System Uncertainty
the main processor to the backup must not exceed 0.5 to
Bank Acceleration, deg/see 2 Uniform 10% 1second.
To evaluate the impact of a processor failure and the
Table 1Expected uncertainties
consecutive computer swap, a sensitivity study to fail-
ure occurrence and duration was carried out.
Other parameters have been also dispersed like the or-
biter mass, the IMU characteristics, ... Initial error in the estimated altitude rate
Stress cases
During the aerocapture the vehicle is fully autonomous.
The vehicle position, its velocity and its attitude are de-
To characterize the robustness of an algorithm, it is also
termined on-board by a strapped down navigation sys-
necessary to consider high uncertainties or off nominal
tem, initializing few hours before reentry (Orbit Deter-
configurations. This is the aim of the stress case analy-
mination) and using IMU sensed accelerations and rota-
sis. Four topics were retained :
tions. The onboard navigated state is not exact and OD
aerodynamic uncertainties error in the initial state cannot be calibrated. It is impor-
tant to determine the sensitivity of the algorithms to this
thruster failure
particular error, especially since guidance accuracy re-
processor failure lies for the most part on the altitude rate feedback. So a
sensitivity study to the initial altitude rate error was car-
on-board vertical velocity estimation error ried out.
Large aerodynamic uncertainties
Cases definitions
The vehicle aerodynamic characteristics directly affect
For each mission, we have defined a set of simulations
the aerocapture performance. The nominal uncertainties
taken into account for Monte Carlo simulations were: to cover the different aspects
- corridor analysis
- +2 degrees on the trim angle of attack
- Monte Carlo simulation
- +10% correlated on the aerodynamic coeffi-
- stress cases
cients
An additional complexity analysis has been done for
These values were doubled for the stress case analysis. each algorithm to evaluate the difficulty to implement
it.
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SIMULATION TOOLS CNES/NASA comparison
Aerocapture Simulator The following results have been obtain with the CNES
simulator (SIMBAD), and the CNES version of the al-
3-DOF and 6-DOF flight simulations have been devel- gorithms. A comparison campaign has been performed
oped at CNES for Mars aerocapture phase studies as by NASA to evaluate the NASA version of two algo-
well as for testing, evaluation and analysis of candidate rithms (APC, TPC), for some missions, with the NASA
guidance algorithms for the PREMIER 2007 Orbiter. simulator (POST), and the Marsgram model Version
2001. The result are very similar.
These simulations include Guidance, on-Board Naviga-
tion and Control functions. The 3-DOF flight simula-
tion principle is presented on Figure 2 • =====================================================
i _i,iil,ili_ii_liiiiiii'iiiiiiii_i_i_iiiiiiiiiiiii
_i_!,i_iiiiii!i_iiiii!i_ii;;iiiiiiiiiiiiiiiiiii!iiii!iiiiii_iiii!_iiiii!iiii!iiii_iiiiiiii!iiiiiiiiiii!iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiliiiiiiiiiiiii!i!iiiiiiiiiiii!!!!!i
_} ........................................
N :::::::::::::::::::::::::::::::::::::::::::::::::::::::
Figure 3 CNES APC corridor analysis
Figure 2 •3-DOF Aerocapture simulation
The NASA-LaRC 3DOF/6DOF simulation software is
based on simulations developed for the Mars 2001
Table 2 APC captured corridor
aerocapture and entry studies, as well as Mars Path-
finder and Mars Polar Lander. (Note the Mars 2001 Or-
NASA APC
biter mission has been modified to use aerobraking and
not aerocapture.) The CNES simulation software was
derived from the Atmospheric Re-entry Demonstrator
trajectory software that was developed from earlier
Hermes project studies. a; _i B
_i¸ B
A cross check of the CNES and NASA 3-DOF trajec-
tory simulator software has been performed. The set of
tests includes environment modeling (gravitational
field, atmosphere, mars characteristics), aerodynamic
characteristics (use of the aerodynamic database de- :_ _ ......
rived from the AFE), the piloting function, and the
computation of the trim angle of attack. The compari-
son leads to very similar results on both simulators
(less than 200 m on the exit conditions at the end of a
guided trajectory). Test cases including guidance, con-
trol and navigation functions were jointly defined and
performed independently on each simulation. Except Figure 4 CNES TPC Monte Carlo simulation
for tests including the navigation function that are not
yet completed, all the cross-tests give very good results.
5
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Result Analysis
p_o,,_o_,capturedcorridor pco,,do,<80%
theoreticalcorridor
Grading Method
Stress Cases
The assessment campaign provided a lot of parameters,
like apoapsis altitude, captured corridor, number of
To characterize the robustness of an algorithm, it is also
elementary operations, ...
necessary to consider high uncertainties or off nominal
Obviously these parameters are not comparable, there- configurations. This is the aim of the stress cases analy-
fore it is necessary to establish agrading method. sis. Four topics were retained :
- aerodynamic uncertainties
The selected grading method consists in giving the best
grade to the best algorithm (20, for example, to copy - thruster failure
French scholar grading), and fixing an apriori perform-
- processor failure
ance corresponding to the worst case (performance as-
sociated to the grade 0). Each algorithm is then given a - on-board vertical velocity estimation error
grade defined by the following relation :
For all the stress cases, the selected performance pa-
rameter is the final apoapsis altitude. Maximal relative
N=20. P-P .......
pz_,_-p...... error with respect to the targeted apoapsis altitude was
selected as the performance parameter (a null value of
The grades obtained on different topics can then be this parameter meaning low sensitivity).
mixed in a "Grade Point Average", taking into account
the relative importance of the different factors by Hap IVan.-.......=0
choosing proper weightings.
p_,,_ max(nominal rain max nominal_) p_........o>0.25
Selected Parameter target target
Performance criteria Definition Thruster failure stress cases
The next step consists in selecting the proper perform- The non acceptable _erformance was fixed to 25%.
ance parameters for each criterion and determining the
associated worst performance.
]Vstt_sstln_s_er =0
Robustness
p_,,oss,hm_>,0_.25
Some simulations were performed to evaluate this par-
ticular point. The proposed grading is based on the cor- Processor failure stress cases
ridor analysis and the stress cases.
Captured Corridor The non acceptable performance was fixed to 50% in
case of a 0.5 second failure duration and 100% in case
The corridor approach consists of a sensitivity analysis of a 1second failure duration.
of the reached apoapsis altitude with respect to the en-
try FPA. 0.5 sec failure duration 1 sec failure duration
The corridor analysis is an essential element of the N_,,.os.s.p.......=0 N_,,.os.s.p........=0
aerocapture characterization. It includes two aspects :
theoretical corridor p_,,-os.s._........>0.5 p_,-oss.._........>1
captured corridor
Initial error in the estimated altitude rate
The selected parameter is the ratio of the captured cor-
The non acceptable performance was fixed to 25%.
ridor to the theoretical corridor.
FPA Ncom&r = 0
I _Pfss_troessssppm.c..e.s..s.o..r > 0=.250
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Accuraci!
AV performance
Threeparametewresreconsiderteodassesthsiscrite- Performance parameter calculation method
rion
The AV2 index performance parameter is defined as the
thefinalorbitapoapsailstitude
maximum 3-sigma value.
thefinalorbitinclination
AV2 N_oo_=0
thein-planAeV(apoapseirsrorcorrection
andperiapsriasisebum) £oo_ =mean+3 cr £oo_>100.
Thetwofirstparametecrosrrespotnodtheaerocapture
Loads
objectives.
The loads corresponds to the thermo-mechanical loads
Thethirdparametmereasurtehsecapabiliotyfthealgo-
applied to the vehicle during the aerocapture. Three ma-
rithmtohaveafinalperiapsaisshighaspossible.
jor parameters have been considered :
Theaccuracisyobtainebdyastatisticaapl proacuhs,- - g-load
ingdifferenattmosphemriocdelsA.1000drawMonte-
- heat rate
Carlosimulatiownasperformefodreachatmospheric
modeAl. statisticaanlalyswisasthencarriedoutglob- - heat load
ally,considerianlglthemodelsT.wostatisticfaiglures
areusedtocharactertihzeeaccurapcyaramete:rs Note that atrajectory which tends to minimize g-load or
heat rate, leads to an increase of the total heat load.
- Themeanvaluewhichhelpstoidentifyasys-
tematibciasofthealgorithmorbittargeting, Performance parameter calculation method
- Thestandadrdeviatio(nYwhichisrepresenta-The selected index performance parameter to character-
ize the load on the vehicle is issued from the 99.7%
tiveofthealgorithmorbittargetinsgensitivity
withrespetcottheconsiderdeidspersions. maximal value encountered during the Monte-Carlo
simulations.
Apoapsis targeting
Performance parameter calculation method
The apoapsis accuracy index performance parameter is
defined as the maximum 3-sigma relative error with re-
Null grade
spect to the targeted apoapsis.
G load
Hap JV_oo,,op =0
The non acceptable performance was fixed to 3.5 earth
g's.
P_..... Imean-targetl +3°- _oo,,o_>0.25
target
Inclination targeting
Performance parameter calculation method
Heat rate
The inclination accuracy index performance parameter
is defined as the maximum 3-sigma error with respect The non acceptable performance was fixed to 500
to the targeted inclination. kW/m 2.
I N_oo,=0
Po_c,=lmean-target 1+3 cr £oo,>1
7
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Heat load Accurac g
The non acceptable performance was fixed to 70
MJ/m 2.
15
_Vheafload =0
10
P_,e_ >70 205
Complexity 0 i r r r
APC EC TPC NPC
This complexity analysis is very simple. No specific
effort was done on the algorithm implementation to im-
prove this particular aspect. It consists of aFORTRAN As apreliminary conclusion on the accuracy criterion :
77 code analysis.
The analytical algorithms (APC,EC) have similar per-
Different aspects have been taken into account : formance with a slight advantage for the APC.
number of executable lines of code
The NPC is too sensitive to on-board navigation errors
number of elementary operations and its constant bank angle optimization pattern leads to
too low periapsis altitudes.
number of complex functions
number of conditional statements The TPC is a little bit less accurate than the analytical
algorithms. However, as soon as navigation errors are
number of loop statements taken into account, the gap in accuracy performance is
greatly reduced.
A specific program was developed to analyze the algo-
rithm Fortran 77 codes. Robustness
Specific grading method
2O
For this criterion, a specific grading method, based on
an empirical rule, was established for each index per-
formance parameter. lO
5
Number of elementary functions
N=20-Nb_elem_operations/50 Oi r r r
APC EC TPC NPC
Number of complex functions
N=20 -Nb_complex_functions/10
As apreliminary conclusion on the robustness criterion:
Number of test instructions
N=20-Nb conditional statements/10 The TPC is the most robust algorithm. It captures al-
most the whole theoretical corridor for all missions. Its
Number of loop targeting performance is not sensitive to an on-board
altitude rate estimation error and quite insensitive to
N=20-Nb_loop_statements
aerodynamic uncertainties and thruster failure.
Number of executable lines
The EC captured corridor performance and stress cases
N=20-Nb exec lines/50
robustness are good and well balanced.
Results
The APC has a good captured corridor performance. It
is sensitive to an on-board altitude rate estimation error.
The following results are the final grade obtain for each
Moreover, the current implemented lateral logic pre-
criteria. They are the result of a complex mix of the dif- sents a lack of robustness to the thruster failure cases.
ferent missions, and parameters.
The NPC is less robust to entry FPA variations than the
three other algorithms. Furthermore, It is too sensitive
8
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totheon-boaardltitudreateestimatioenrrotrobecom-
petitivaetthisstage.
Loads
2O
10
155
0 i i i i i
APC EC TPC NPC
Comments on the chart :
APC, EC and TPC are well adapted to control the vehi-
cle loads, whereas NPC would require a constrained NPC implementation is far more complex than the oth-
optimization scheme to control the loads. ers. Furthermore, this higher complexity does not pro-
vide better robustness, accuracy or load control.
Complexity
TPC is a very simple and robust algorithm. The current
version does not include an on-board estimation of the
density scale height. This explains the very poor accu-
racy of the algorithm for the Dust Storm mission.
APC has been tuned to be very accurate, but it is less
robust than TPC and EC, especially for the stress cases.
20,010,015ii,i0ii i5ii,"i0iiiiiiiiiiiii
Some additional work is needed to solve the thruster
failure sensitivity by modifying the lateral logic.
0,0 .....
APC EC TPC NPC EC has well balanced performance. Some additional
work to fine tune the algorithm should be done in order
to improve the heat load control while keeping accept-
able g-load / heat rate levels.
TPC implementation (on-board code development and
testing) is the less expensive. APC and EC are competi-
tive, their implementation being also very simple. NPC
complexity remains too important to be selected as a
viable candidate for afirst aerocapture mission.
Final Ranking
The following chart gives the detailed profile of each 21004,,,000162,0,081,0:4+':i+_:1+6:-,0---:+:+:+:+:"""
algorithm and presents the ranking for each particular
characteristic : corridor, stress cases, dust storm accu-
APC EC TPC NPC
racy and robustness, perfect and real navigation accu-
racy, loads and complexity. ] Robustness n Accuracy [] Loads []Complexity
This campaign permitted to compare the four guidance
algorithms which have been implemented at CNES:
- the Analytical Predictor-Corrector (APC)
- the Energy Controller (EC)
- the Terminal Point Controller (TPC)
- the Numerical Predictor-Corrector (NPC)
American Institute of Aeronautics and Astronautics
Thiscampaigwnasexhaustievneougthoassesthseal-
5. J. Masciarelli, S. Rousseau, H. Fraysse, E. Pc-
gorithmperformanaccecordintogthefollowingfour
rot : %n analytic aerocapture guidance algo-
relevancrtiteria:
rithm for the Mars Sample Return Orbiter",
- robustness AIAA-2000-4116,14-17 August 2000
- accuracy 6. J.D. Gamble, C.J. Cerimele, T.E. Moore and J.
Higgins : _Atmospheric Guidance Concepts
- loadcontrol
for an Aeroassist Flight Experiment", Journal
of the Astronautical Sciences, Vol. 36, Nos. 1/2,
- complexity
Special Issue on Hypervelocity Flight, Janu-
Theresultwserepresenteodnthe30th,31stofJanuary ary-June 1988
duringajointCNES-NASreAviewT.hemethodology
7. S. Rousseau, H. Fraysse, C. Hourtolle : _ The
fortheperformanacsesessmaesnwtellasforthegrad-
aerocapture phase of the Mars Sample Return
ingofthedifferenatlgorithmwsasaccepteadndfinal
Orbiter", MS00/60, Space Dynamics Sympo-
rankingwsereestablisheadccordintgothedifferent
sium 26-30 June 2000
scenari(odsifferenstetofweightings).
Theconclusiownhsichcanbedrawanrethefollowing: 8. Cerimele, C.J.; Gamble, J.D.: _A Simplified
Guidance Algorithm for Lifting Aeroassist
Orbital Transfer Vehicles," AIAA-85-0348,
Whatevethreweightingasre,NPCisfarfrombeing
AIAA 23rd Aerospace Sciences Meeting,
competitivIem.provemeonftthealgorithmwouldim-
Reno, Nevada, January 1985.
plyanincreasoefthecomplexitwyi,thougtuaranteeing
betteprerformanccoemparteodtheothearlgorithms.
9. Ro T.U., Queen E.M., "Mars aerocapture ter-
WhatevethreweightingTsP, Cisrankefdirst.Itsper- minal point guidance and control". Paper No
98-4571, AIAA Atmospheric Flight Mechan-
formancaereexcellenetxcepftortheDustStormsce-
ics Conference, Boston, MA, August 1998
narioT.heuseofthisalgorithimshighlyrecommended,
butspeciaelfforht astobedonetoimplemeandtensity
10. Bryant L.E., Tigges M., Iacomini C., "Analytic
scalheeighotn-boaerdstimator.
Drag Control for precision landing and aero-
TheanalyticAalPCandECareexcelleanltternativteos capture", paper No 98-4572, AIAA Atmos-
TPC.Theyareveryclosedbothconceptuaallnydin pheric Flight Mechanics
termsofperformanwceit,haslighrtobustneasdsvan-
11. Wingrove Rodney G., "Survey of Atmospheric
tageforECandaslighatccuracaydvantafgoerAPC.
Re-Entry Guidance and Control Methods".
AIAA Journal - Vol. 1 - N° 9 - September
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American Institute of Aeronautics and Astronautics