Statistical risk estimation for communication system design: Development of optimization frameworks

The design of a spacecraft is an evolutionary process that starts from requirements and evolves over time across different design phases. During this process, a lot of changes can happen. They can affect mass and power at component level, at subsystem level, and even at system level. Each spacecraft has to meet overall constraints in terms of mass and power: for this reason, it's important to be sure that the design does not exceed these limitations. Current practice in system modeling deals with this problem by allocating margins on single components and on each of the subsystems. However, a statistical characterization of these fluctuations in mass and power is missing, and the consequence is a design that either is too risky and does not fit the mission constraints, or is too conservative and generates an inefficient utilization of resources.

[1]  A. Tversky,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[2]  E. Parzen On Estimation of a Probability Density Function and Mode , 1962 .

[3]  Alessandra Babuscia,et al.  A Quantitative Approach to Perform Expert Elicitation for Space Communication System Design and Risk Analysis: Methodology and Experimental Results , 2011 .

[4]  Paolo Giorgini,et al.  Using Risk Analysis to Evaluate Design Alternatives , 2006, AOSE.

[5]  Alessandra Babuscia,et al.  Statistical Risk Estimation for Communication System Design , 2013, IEEE Systems Journal.

[6]  De Weck,et al.  Multivariable isoperformance methodology for precision opto-mechanical systems , 2002 .

[7]  Marshall B. Jones,et al.  2.1.1 Isoperformance: Analysis and Design of Complex Systems with Known or Desired Outcomes , 2004 .

[8]  Joseph A. Shaw,et al.  Infrared Cloud Imager Development for Atmospheric Optical Communication Characterization, and Measurements at the JPL Table Mountain Facility , 2013 .

[9]  Jeremy E. Oakley,et al.  Uncertain Judgements: Eliciting Experts' Probabilities , 2006 .

[10]  Olivier L. de Weck,et al.  Staged Deployment of Communications Satellite Constellations in Low Earth Orbit , 2004, J. Aerosp. Comput. Inf. Commun..

[11]  Alessandra Babuscia,et al.  Statistical Rick Estimation for Communication System Design --- A Preliminary Look , 2012 .

[12]  Student BELIEF IN THE LAW OF SMALL NUMBERS , 1994 .

[13]  Arnold Neumaier,et al.  Potential Based Clouds in Robust Design Optimization , 2009 .

[14]  Charles D. Brown Elements of Spacecraft Design , 2002 .

[15]  Jon C. Helton,et al.  Challenge Problems : Uncertainty in System Response Given Uncertain Parameters ( DRAFT : November 29 , 2001 ) , 2001 .

[16]  Arnold Neumaier,et al.  Uncertainty modeling in autonomous robust spacecraft system design , 2007 .

[17]  John Quigley,et al.  Reaction to ‘An approach to perform expert elicitation for engineering design risk analysis: methodology and experimental results’ , 2014 .

[18]  David W. Miller,et al.  Assessing the performance of a heuristic simulated annealing algorithm for the design of distributed satellite systems , 2001 .

[19]  Rania Hassan,et al.  Approach to Discrete Optimization Under Uncertainty: The Population-Based Sampling Genetic Algorithm , 2007 .

[20]  Allan S Detsky,et al.  Everyone's a little bit biased (even physicians). , 2008, JAMA.

[21]  David W. Miller,et al.  Multi-Objective, Multidisciplinary Design Optimization Methodology for Distributed Satellite Systems , 2004 .

[22]  L. Breiman,et al.  Variable Kernel Estimates of Multivariate Densities , 1977 .

[23]  C. E. Gilchriest Spacecraft mass trade-offs versus radio-frequency power and antenna size at 8 GHz and 32 GHz , 1987 .

[24]  Hany H. Ammar,et al.  Model-based performance risk analysis , 2005, IEEE Transactions on Software Engineering.

[25]  A. Dasgupta Asymptotic Theory of Statistics and Probability , 2008 .

[26]  USRA NASA Ames,et al.  DESIGN TEAMS , COMPLEX SYSTEMS AND UNCERTAINTY , 2007 .

[27]  Rania Hassan,et al.  ARCHITECTING A COMMUNICATION SATELLITE PRODUCT LINE , 2004 .

[28]  Bradford W. Parkinson,et al.  System Design under Uncertainty: Evolutionary Optimization of the Gravity Probe-B Spacecraft , 1994, PPSN.

[29]  Dimitris Bertsimas,et al.  Nonconvex Robust Optimization for Problems with Constraints , 2010, INFORMS J. Comput..

[30]  Cyrus D. Jilla,et al.  Multidisciplinary Design Optimization Methodology for the Conceptual Design of Distributed Satellite Systems , 2002 .

[31]  M. C. Jones,et al.  E. Fix and J.L. Hodges (1951): An Important Contribution to Nonparametric Discriminant Analysis and Density Estimation: Commentary on Fix and Hodges (1951) , 1989 .

[32]  C. D. Kemp,et al.  Density Estimation for Statistics and Data Analysis , 1987 .

[33]  Rania Hassan,et al.  DISCRETE DESIGN OPTIMIZATION UNDER UNCERTAINTY: A GENERALIZED POPULATION-BASED SAMPLING GENETIC ALGORITHM , 2004 .

[34]  M. Rosenblatt Remarks on Some Nonparametric Estimates of a Density Function , 1956 .

[35]  James R. Wertz,et al.  Space Mission Analysis and Design , 1992 .

[36]  C. Quesenberry,et al.  A nonparametric estimate of a multivariate density function , 1965 .

[37]  Natalia Alexandrov,et al.  Multidisciplinary design optimization : state of the art , 1997 .

[38]  Raymond J. Sedwick,et al.  Application of Multidisciplinary Design Optimization Techniques to Distributed Satellite Systems , 2000 .

[39]  David W. Miller,et al.  Mit castor satellite: Design, implementation, and testing of the communication system ☆ , 2012 .

[40]  R. Cooke Experts in Uncertainty: Opinion and Subjective Probability in Science , 1991 .

[41]  L. Meshkat,et al.  A Holistic Approach for Risk Management During Design , 2007, 2007 IEEE Aerospace Conference.

[42]  Arnold Neumaier,et al.  Autonomous robust design optimisation with potential clouds , 2009 .

[43]  Jaroslaw Sobieszczanski-Sobieski,et al.  Multidisciplinary aerospace design optimization - Survey of recent developments , 1996 .