Title :
Single frequency GNSS integer ambiguity resolution with adaptive genetic algorithm
Author :
Dingjie Xu ; Mingkai Liu ; Liye Zhu
Author_Institution :
Coll. of Autom., Harbin Eng. Univ., Harbin, China
Abstract :
According to genetic algorithm (GA) has the advantage to resolve the global numerical value optimization problems in robust and parallel way, the adaptive genetic algorithm(AGA) is applied to resolve the single frequency GNSS carrier phase integer ambiguity in this paper. The fitness function based on the non-linear integer weighted Least-square principle is constructed, while the baseline length is to determine the integer ambiguities search range as the constraint. Finally the adaptive genetic algorithm (AGA) is applied to resolve the integer ambiguity. Simulation numerical results show that the resolution with adaptive genetic algorithm is more robust and reliable than simple genetic algorithm (SGA).
Keywords :
genetic algorithms; least squares approximations; satellite navigation; AGA; SGA; adaptive genetic algorithm; baseline length; fitness function; global numerical value optimization problem; integer ambiguity search range; nonlinear integer weighted least-square principle; simple genetic algorithm; simulation numerical results; single-frequency GNSS carrier phase integer ambiguity resolution; Educational institutions; Estimation; Genetic algorithms; Global Positioning System; Robustness; Sociology; Statistics;
Conference_Titel :
Information Science and Technology (ICIST), 2013 International Conference on
Conference_Location :
Yangzhou
Print_ISBN :
978-1-4673-5137-9
DOI :
10.1109/ICIST.2013.6747716