Solving Integer Ambiguity Based on Genetic Algorithm with Improved Simulated Annealing

doi:10.13438/j.cnki.jdzk.2018.04.003

Abstract

Abstract:

Cholesky decomposition is adopted to decorrelate the float solution and its covariance matrix,and the correlation of each ambiguity float estimation can be eliminated.Then simulated annealing is applied to the population iteration,and the integer ambiguity optimization results can be determined by using the improving algorithm.The simulation results show that the improved algorithm can reduce the speed of convergence and improve the efficiency of the algorithm.

Key words: inter ambiguity, simulated annealing, genetic algorithm, optimal solution

LI Honggang,WANG Yaqi,LI Xueqing,KANG Junjian. Solving Integer Ambiguity Based on Genetic Algorithm with Improved Simulated Annealing[J]. Journal of Jishou University（Natural Sciences Edition), DOI: 10.13438/j.cnki.jdzk.2018.04.003.

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