DOI QR코드

DOI QR Code

A Study on the Collision Avoidance Maneuver Optimization with Multiple Space Debris

  • Kim, Eun-Hyouek (Department of Satellite Systems and Applications Engineering, University of Science and Technology) ;
  • Kim, Hae-Dong (Department of Satellite Systems and Applications Engineering, University of Science and Technology) ;
  • Kim, Hak-Jung (Satellite Information Research Center, Korea Aerospace Research Institute)
  • Received : 2011.11.28
  • Accepted : 2012.01.31
  • Published : 2012.03.15

Abstract

In this paper, the authors introduced a new approach to find the optimal collision avoidance maneuver considering multi threatening objects within short period, while satisfying constraints on the fuel limit and the acceptable collision probability. A preliminary effort in applying a genetic algorithm (GA) to those kinds of problems has also been demonstrated through a simulation study with a simple case problem and various fitness functions. And then, GA is applied to the complex case problem including multi-threatening objects. Two distinct collision avoidance maneuvers are dealt with: the first is in-track direction of collision avoidance maneuver. The second considers radial, in-track, cross-track direction maneuver. The results show that the first case violates the collision probability threshold, while the second case does not violate the threshold with satisfaction of all conditions. Various factors for analyzing and planning the optimal collision avoidance maneuver are also presented.

Keywords

References

  1. Alfano S, Collision avoidance maneuver planning tool, in Proceedings of the 15th AAS/AIAA Astrodynamics Specialist Conference, Lake Tahoe, CA, 7-11 Aug 2005.
  2. Alfano S, Review of conjunction probability methods for short-term encounters, in Proceedings of the AAS/AIAA Space Flight Mechanics Meeting, Sedona, AZ, 28 Jan-1 Feb 2007.
  3. Deb K, Agrawal S, A niched-penalty approach for constraint handling in genetic algorithms, in Artificial neural nets and genetic algorithms: Proceedings of the International Conference in Portoroz, Slovenia, 1999, eds. Dobnikar A, Steele NC, Pearson DW, Albrecht RF (Springer, Wien, 1999), 235-243.
  4. Goldberg DE, Genetic algorithms in search, optimization, and machine learning (Addison-Wesley, Reading, 1989).
  5. Helio JCB, Afonso CCL, An adaptive penalty method for genetic algorithms in constrained optimization problems, in Frontiers in evolutionary robotics [Internet], cited 2012 Feb 20, available from: http://www.intechopen.com/articles/show/title/an_adaptive_penalty_method_for_genetic_algorithms_in_constrained_optimization_problems
  6. Kim HD, Bang H, Jung OC, Genetic design of target orbits for a temporary reconnaissance mission, JSpRo, 46, 725-728 (2009). http://dx.doi.org/10.2514/1.41620
  7. Klinkrad H, Space debris models and risk analysis (Praxis Publishing Ltd., Chichester, UK, 2006), 215-240.
  8. Mariella G, GMV astrodynamics tools and techniques overview, in the 3rd ESA Workshop on Astrodynamics Tools and Techniques, Noordwijk, The Netherlands, 2-5 Oct 2006.
  9. Morris R, Space surveillance contributions to the STS 107 accident investigation, in Proceedings of the 14th AAS/AIAA Space Flight Mechanics Conference, Maui, Hawaii, 8-12 Feb 2004.
  10. Liemer R, Chyba CF, A verifiable limited test ban for anti-satellite weapons, The Washington Quarterly, 33, 149-169 (2010). http://dx.doi.org/10.1080/0163660X.2010.492346
  11. Sanchez-Ortiz N, Bello-Mora M, Klinkrad H, Collision avoidance maneuvers during spacecraft mission lifetime: risk reduction and required ΔV, AdSpR, 38, 2107-2116 (2006). http://dx.doi.org/10.1016/j.asr.2005.07.054

Cited by

  1. Collision Avoidance Maneuver Planning Using GA for LEO and GEO Satellite Maintained in Keeping Area vol.13, pp.4, 2012, https://doi.org/10.5139/IJASS.2012.13.4.474
  2. Multiobjective optimization for collision avoidance maneuver using a genetic algorithm vol.230, pp.8, 2016, https://doi.org/10.1177/0954410015611699
  3. Analytical Design of the Space Debris Collision Avoidance Maneuver based on Relative Dynamics vol.19, pp.11, 2013, https://doi.org/10.5302/J.ICROS.2013.13.8016
  4. Collision avoidance maneuvers for multiple threatening objects using heuristic algorithms vol.229, pp.2, 2015, https://doi.org/10.1177/0954410014530678
  5. Analysis of Precise Orbit Determination of the KARISMA Using Optical Tracking Data of a Geostationary Satellite vol.42, pp.8, 2014, https://doi.org/10.5139/JKSAS.2014.42.8.661
  6. Optimization of collision avoidance maneuver planning for cluster satellites in space debris explosion situation vol.232, pp.3, 2018, https://doi.org/10.1177/0954410016682270