| 基于模拟退火遗传算法求解整周模糊度 |
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| 引用本文： | 李洪刚,王亚琦,李雪晴,亢俊健.基于模拟退火遗传算法求解整周模糊度[J].吉首大学学报(自然科学版),2018,39(4):9. |
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| 作者姓名： | 李洪刚 王亚琦 李雪晴 亢俊健 |
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| 作者单位： | （河北地质大学，河北 石家庄 050031） |
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| 基金项目： | 国家自然科学基金资助项目（61503260）；河北省研究生创新资助项目（CXZZSS2018075） |
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| 摘 要： | 采用乔里斯基分解对浮点解和协方差矩阵进行降相关处理，以降低整周模糊度各分量之间的相关性，然后在遗传算法的种群迭代中加入模拟退火的思想，并将改进的遗传算法应用到整周模糊度的搜索解算上，最终求得整周模糊度的最优解.仿真结果表明，在整周模糊度的解算过程中改进的算法能降低算法的收敛速度，提高算法的运行效率.
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Solving Integer Ambiguity Based on Genetic Algorithm with Improved Simulated Annealing |
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| 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 Science Edition),2018,39(4):9. |
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| Authors: | LI Honggang WANG Yaqi LI Xueqing KANG Junjian |
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| Institution: | (Hebei GEO University,Shijiazhuang 050031,China) |
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| 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. |
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| Keywords: | inter ambiguity simulated annealing genetic algorithm optimal solution |
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