Title :
Multilateration Station Location Study Based on Genetic Algorithm
Author :
Li Bo ; Zhang Xuejun ; Zhao Shuang
Author_Institution :
Beihang Univ., Beijing, China
Abstract :
Multilateration requires to achieve maximum coverage area at the condition of meeting positioning precision. The station location is directly related to positioning accuracy and coverage area. This paper applies GA(genetic algorithm) to multilateration station location, and quantifies coverage area into the fitness function. This method effectively increases coverage area under the condition of meeting the positioning accuracy, compared with the results of the traditional ones. Simulation results show the effectiveness of GA.
Keywords :
facility location; genetic algorithms; position measurement; transportation; fitness function; genetic algorithm; maximum coverage area; multilateration station location; positioning accuracy; Accuracy; Aircraft; Encoding; Gallium; Genetic algorithms; Optimization; Process control; GA; GDOP; Multilateration;
Conference_Titel :
Computational Intelligence and Design (ISCID), 2010 International Symposium on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4244-8094-4
DOI :
10.1109/ISCID.2010.23