Quantitative Assessment of Technology Infusion in Communications Satellite Constellations

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Quantitative Assessment of TechnologyInfusion in
Communications SatelliteConstellations
Unit 3

• Olivier de Weck and Darren Chang, MIT, U.S.A.
• Ryutaro Suzuki, CRL, Tokyo, Japan
• Eihisa Morikawa, NeLS, Kanagawa, Japan

21st International Communications Satellite
Systems Conference, 15-19 April 2003, Yokohama,
Japan
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Outline

• Introduction and Motivation
• Previous Work in Technology Assessment
• Quantitative Technology Infusion Assessment
  Methodology
• Application to Satellite Communications
  Constellations
• Conclusions
• Future Work

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Motivation

• The architecture of satellite communications
  systems (concept) must be carefully selected
• Selection of architectures can be done
  quantitatively based on performance, cost and
  capacity predictions see AIAA-2002-1866
• A number of new technologies are currently under
  development for GEO and LEO Systems, e.g.
• Large Deployable Reflector (LDR) Antennas
• Optical Inter-satellite Links (OISL)
• System Designers/Architects must often choose
  between competing technologies need a
  quantitative method
• Generally, better understand the relationship
  between architectures and technologies

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Conceptual Design Space
Can we quantify the conceptual system design
problem using simulation and optimization?
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Key Idea Pareto Impact
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Previous Work

• Metrics for comsat architecture evaluation cost
  per function CPF /min at a fixed data
  rate R, BER pb and link margin (Hastings, Shaw.)
• Architecture Evaluation and Selection using MDO
  (multi-disciplinary design optimization)
  Miller, Jilla, de Weck
• Research in new generations of satellite
  constellations (e.g. NeLs, R. Suzuki) and new
  technologies
• Technology assessment proposed by Management of
  Technology (MOT) Utterback, van Wyk, Henderson
  and Clark
• Technology Selection Mavris, DeLaurentis

gt Perceive a missing link between architecture
evaluation and technology selection
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Assumptions

• Possible to create high-fidelity simulations of
  satellite communications systems during
  conceptual design
• Performance per channel is fixed
• Data Rate
• Bit-Error-Rate
• Link Fading Margin
• Tradeoff between system capacity and lifecycle
  cost
• Architectures are realizable with existing,
  mature technologies

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Proposed Methodology
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Steps 1-3
Step 1 Baseline Trade Space Exploration -
Obtain Baseline Pareto Frontier Po
Step 2 Technology Identification,
Classification, Modeling - Understand
technology dependencies Tc, Td - Technology
modeling physics based, prototype data,
empirical relationships (expert interviews)
Step 3 Technology Infusion Interface Development
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Steps 4-6
Step 4 Individual Technology Assessment
Step 5 Assessment of allowable combinations
of technologies Step 6 Comparison
and Interpretation - based on Pareto Impact
Metrics (4)
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Application LEO Com Sat
LEO Constellation 50 satellites 5 planes h800 km
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Benchmarking

• Benchmarking validating a simulation
• by comparing the predicted response against
  reality.

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Design Trade Space
Design Vector
1728 Full Factorial Combinatorial Design Space
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Baseline Case
Baseline Design Space Uses only Existing,
Mature Technologies
Channel Perf
R4.8 kbps pb0.001 LM16 dB
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Technology Portfolio
Technology Dependency Matrix
T1 T2 T3 T4
T1 0 1 0 0
T2 0 0 0 0
T3 0 0 0 0
T4 0 0 1 0
T1 Optical Inter-Satellite Links (OISL) T2
Asynchronous Transfer Mode (ATM) T3 Large
Deployable Reflectors (LDR) T4 Digital/Analog
Beamforming (DBF)
Techno Description Satellite () (-)
OISL Replace RF ISL Spot-4 Rgt10Gbps Pointing requirement
ATM Packet/circuit switching ACTS Efficiency Mass penalty
LDR DA up to 20m ETS-VIII Gain 38-45 dBi Large Stowage Volume
DBF Ground fixed cells TBD Handover Complexity
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Example Impact of LDR
Large Deployable Reflectors (LDR)
ETS-VIII
E.g. for DA6m -gt GT39 dBi, l0.19m,
TFU2.45 M
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Pareto Impact Example LDR
Po is the normalized Pareto front with baseline
technologies alone.
P3 is the normalized Pareto front with LDR.
Decreased utopia point distance
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Overview Results - MP
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Conclusions

• Presented a methodology for quantitatively
  assessing technology impact on Communication
  Satellites
• Choose between mature, existing technologies
  versus newly emerging, competing technologies
• Technology portfolio technology investment
  decisions
• Use simulation to predict performance, cost and
  capacity for a set of candidate architectures
• Careful benchmarking required
• Modular simulation architecture eases
  investigation of a large set of technologies
• Current technologies under development for NeLS
  make sense for broadband, multimedia system
• Engineering Systems Industry Study will be
  available

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Future Work

• Harden and verify this methodology by deploying
  in an industrial/satellite manufacturer setting,
  apply to GEO
• Uncertainty in effect on Pareto front P due to
  technology maturity e.g. measured via NASAs
  Technology Readiness Levels (TRL) probabilistic
• Expand work to more than two (2) objectives
• How to deal with disruptive technologies that
  enable new architectures in that case dont
  have a baseline Pareto front to compare to, e.g.
  introduction of ISL when only bent-pipe was
  known.
• Understand relationship between Pareto Impact
  metrics and technology obsolescence