Title :
Initial orbit determination based on sparse space-based angle measurement and genetic algorithm
Author :
Lei Liu ; Geshi Tang ; Songjie Hu
Author_Institution :
Sci. & Technol. on Aerosp. Flight Dynamics Lab., Beijing, China
Abstract :
This paper studies the initial orbit determination based on sparse space-based angle measurement and genetic algorithm. The double rho iteration model used by the space-based initial orbit determination is briefly introduced firstly. Because of problems of iteration divergences and self-solutions in the space-based initial orbit determination, the genetic algorithm of SGA and MPGA are then adopted to solve the problems. According to the research results, the space-based initial orbit determination generally got more satisfied solutions by the genetic algorithm than common iteration algorithms. Furthermore, the MPGA genetic algorithm is very effective to overcome the above drawbacks on the initial orbit determination based on sparse space-based angle measurement.
Keywords :
aerospace instrumentation; angular measurement; genetic algorithms; iterative methods; MPGA; SGA; double rho iteration model; iteration algorithms; iteration divergences; multipopulation genetic algorithm; single genetic algorithm; space-based initial orbit determination; sparse space-based angle measurement; Extraterrestrial measurements; Genetic algorithms; Optimization; Orbits; Sociology; Statistics; Vectors; Double Rho Iteration Model; Genetic Algorithm; Initial Orbit Determination; Sparse Space-based Angle Measurement;
Conference_Titel :
Information and Automation (ICIA), 2013 IEEE International Conference on
Conference_Location :
Yinchuan
DOI :
10.1109/ICInfA.2013.6720412