Optimal small satellite orbit design based on robust multi-objective optimization method

Abstract This paper investigates an optimal small satellite orbit design problem subject to the atmospheric drag uncertainty, and the small satellite is assumed to have no orbital control systems due to volume and mass constraints. The optimization objective of maximum target observation time is considered, which is constrained by the priority and minimum observation duration of each target site. Given the adverse impacts of atmospheric drag uncertainty on the designed orbit, the optimal solution is expected to maximize observation duration for given target sites while being less sensitive to substantial variations of atmospheric coefficients involved in atmospheric drag modeling. As a result, a robust orbit design approach is proposed by combining the robust optimization model with multi-objective optimization algorithm. Finally, the Monte Carlo simulation results are provided to demonstrate that the robust orbit solutions are more reliable compared to the nominal orbit solution designed from the traditional single-objective stochastic optimization algorithm.

[1]  André Langevin,et al.  A robust optimization approach for the road network daily maintenance routing problem with uncertain service time , 2016 .

[2]  Dimitris Bertsimas,et al.  On the Power of Robust Solutions in Two-Stage Stochastic and Adaptive Optimization Problems , 2010, Math. Oper. Res..

[3]  Darinka Dentcheva,et al.  Robust stochastic dominance and its application to risk-averse optimization , 2010, Math. Program..

[4]  Yoaz Bar-Sever,et al.  Effects of thermosphere total density perturbations on LEO orbits during severe geomagnetic conditions (Oct–Nov 2003) using DORIS and SLR data , 2005 .

[5]  M. Stein Large sample properties of simulations using latin hypercube sampling , 1987 .

[6]  Daniele Mortari,et al.  Orbit Design for Ground Surveillance Using Genetic Algorithms , 2006 .

[7]  Qi Zhang,et al.  An adjustable robust optimization approach to scheduling of continuous industrial processes providing interruptible load , 2016, Comput. Chem. Eng..

[8]  Kyu-Hong Choi,et al.  Satellite orbit determination using a batch filter based on the unscented transformation , 2010 .

[9]  P. L. Palmer,et al.  Repeat-Groundtrack Orbit Acquisition and Maintenance for Earth-Observation Satellites , 2007 .

[10]  Y. Jiao,et al.  MOEA/D-SQA: a multi-objective memetic algorithm based on decomposition , 2012 .

[11]  Xiaofeng Fu,et al.  Design and Maintenance of Low-Earth Repeat-Ground-Track Successive-Coverage Orbits , 2012 .

[12]  David Finkleman,et al.  A critical assessment of satellite drag and atmospheric density modeling , 2014 .

[13]  David Krejci,et al.  A survey and assessment of the capabilities of Cubesats for Earth observation , 2012 .

[14]  Ryan P. Russell,et al.  Long-Lifetime Lunar Repeat Ground Track Orbits , 2007 .

[15]  A. Hedin MSIS‐86 Thermospheric Model , 1987 .

[16]  John E. Mottershead,et al.  A review of robust optimal design and its application in dynamics , 2005 .

[17]  Nima Assadian,et al.  Repeat ground track orbit design with desired revisit time and optimal tilt , 2015 .

[18]  Feng Luan,et al.  A Particle Swarm Optimization Algorithm With Novel Expected Fitness Evaluation for Robust Optimization Problems , 2012, IEEE Transactions on Magnetics.

[19]  M. Guelman,et al.  Electric Propulsion for Remote Sensing from Low Orbits , 1999 .

[20]  Kalyanmoy Deb,et al.  Dynamic Multi-objective Optimization and Decision-Making Using Modified NSGA-II: A Case Study on Hydro-thermal Power Scheduling , 2007, EMO.

[21]  Gaëtan Kerschen,et al.  Robust optimal rendezvous using differential drag , 2014 .

[22]  D. Vallado Fundamentals of Astrodynamics and Applications , 1997 .

[23]  Chao Xiong,et al.  An empirical relation to correct storm-time thermospheric mass density modeled by NRLMSISE-00 with CHAMP satellite air drag data , 2009 .

[24]  M. Cheng,et al.  GGM02 – An improved Earth gravity field model from GRACE , 2005 .

[25]  Joaquim R. R. A. Martins,et al.  Large-Scale Multidisciplinary Optimization of a Small Satellite’s Design and Operation , 2014 .

[26]  Cong Li,et al.  Target detection approach for UAVs via improved Pigeon-inspired Optimization and Edge Potential Function , 2014 .

[27]  G. Petit,et al.  IERS Conventions (2010) , 2010 .

[28]  Katharine Smith,et al.  Launch and deployment of distributed small satellite systems , 2015 .

[29]  Silvana M. B. Afonso,et al.  An efficient procedure for structural reliability-based robust design optimization , 2016 .

[30]  Behnam Saboori,et al.  Multiobjective Optimization in Repeating Sun-Synchronous Orbits Design for Remote-Sensing Satellites , 2014 .

[31]  Qingfu Zhang,et al.  Multiobjective Optimization Problems With Complicated Pareto Sets, MOEA/D and NSGA-II , 2009, IEEE Transactions on Evolutionary Computation.

[32]  T. Sowlati,et al.  A hybrid multi-stage stochastic programming-robust optimization model for maximizing the supply chain of a forest-based biomass power plant considering uncertainties , 2016 .

[33]  A. Hedin Extension of the MSIS Thermosphere Model into the middle and lower atmosphere , 1991 .

[34]  Valerio Lattarulo,et al.  Multidisciplinary Optimization Under High-Dimensional Uncertainty for Small Satellite System Design , 2016 .

[35]  M. D. McKay,et al.  A comparison of three methods for selecting values of input variables in the analysis of output from a computer code , 2000 .

[36]  Simone D'Amico,et al.  Impact of Orbit Prediction Accuracy on Low Earth Remote Sensing Flight Dynamics Operations , 2004 .

[37]  O. Abdelkhalik,et al.  Optimization of space orbits design for Earth orbiting missions , 2011 .

[38]  Brett Newman,et al.  Determining an Earth Observation Repeat Ground Track Orbit for an Optimization Methodology , 2012 .

[39]  Xu Andy Sun,et al.  Adaptive Robust Optimization With Dynamic Uncertainty Sets for Multi-Period Economic Dispatch Under Significant Wind , 2015 .

[40]  D. MacManus,et al.  Correction: Aerodynamic interference on a finned slender body , 2016 .