基于自适应差分进化算法的高维模糊度搜索

孙妍艳; 刘翠芝

doi:10.13442/j.gnss.1008-9268.2018.01.007

基于自适应差分进化算法的高维模糊度搜索

doi: 10.13442/j.gnss.1008-9268.2018.01.007

东北大学资源与土木工程学院测绘工程系,辽宁沈阳 110819

详细信息

作者简介:
孙妍艳(1983-),女,硕士研究生,主要研究方向为大地测量。

通信作者:
孙妍艳E-mail: 767564911@qq.com[

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- 被引次数: 0
出版历程
- 刊出日期: 2018-03-28

Searching High-dimension Ambiguity Based on Self-adaptive Differential Evolution Algorithm

Department of Surveying and Mapping Engineering in College of Resources and CivilEngineering, Northeastern University, Shenyang 110819, China

摘要

摘要: 针对高维整周模糊度解算问题,提出了一种新的搜索算法,采用自适应差分进化算法,利用其特有的全局、快速、并行搜索的特性对高维模糊度进行固定。根据所求解问题的特点,在原有自适应差分进化算法的基础上对部分参数进行重新设定,从而实现模糊度的快速搜索。并以LAMBDA算法的解算结果和运算速率为依据,验证本算法结果的正确性和解算的快速性。通过模拟和实测不同维数的数据进行验证,表明该算法对高维模糊度解算具有一定的应用参考价值,且具有较好的可靠性和鲁棒性。
- 高维整周模糊度解算 /
- 搜索算法 /
- 自适应差分进化算法 /
- LAMBDA算法
Abstract: In this paper, a new algorithm is proposed to solve the problem of high dimensional ambiguity resolution. The self-adaptive differential evolution algorithm is used to fix the high dimensional ambiguity with its global, fast and parallel search. According to the characteristics of the problem to be solved, some parameters are reset on the basis of the original adaptive differential evolution algorithm so as to realize the quick search of the ambiguity. Based on the solution and operation rate of LAMBDA algorithm, the correctness of the algorithm and the rapidity of solution are verified. It is proved that the algorithm has certain application reference value for high dimensional ambiguity resolution, and it has good reliability and robustness by simulating and measuring the data with different dimensions.
- High-dimensional integer ambiguity resolution /
- searching algorithm /
- self-adaptive differential evolution algorithm /
- LAMBDA algorithm

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参考文献(18)

[1]	LI Z, GAO Y. A method for the construction of[JP] high-dimensional transformation matrices in Lambda ［J］.Geomatica,1998(52):433-439.
[2]	TEUNISSEN P J G. A General multivariate formulation of the multi-antenna GNSS attitude determination problem ［J］. Artificial Satellites, 2008, 42(2): 97-111.
[3]	卢立果, 刘万科, 李江卫. 降相关对模糊度解算中搜索效率的影响分析［J］. 测绘学报, 2015, 44(5): 481-487.
[4]	BORNO M A, CHANG X W, XIE X H. On ‘decorrelation’ in solving integer least
[5]	CHANG X W, YANG X, ZHOU T. MLAMBDA: a modified LAMBDA method for integer least-squares estimation ［J］. Journal of Geodesy, 2005, 79(9): 552-565.
[6]	刘万科,卢立果,单弘煜. 一种快速解算高维模糊度的LLL分块处理算法［J］. 测绘学报, 2016(2): 147-156.
[7]	卢立果,刘万科,李江卫. 一种有效的LLL规约算法［J］. 武汉大学学报(信息科学版), 2016(8): 1118-1124.
[8]	刘智敏,刘经南,姜卫平, 等. 遗传算法解算GPS短基线整周模糊度的编码方法研究［J］. 武汉大学学报(信息科学版), 2006(7): 607-609，631.
[9]	阳仁贵,欧吉坤,王振杰, 等. 用遗传算法搜索GPS单频单历元整周模糊度［J］. 武汉大学学报(信息科学版), 2005（3): 251-254,259.
[10]	VESTERSTROM J, THOMSEN R. A comparative study of differential evolution, particle swarm optimization, and evolutionary algorithms on numerical benchmark problems［C］// Evolutionary Computation, 2004. CEC2004. Congress on. IEEE, 2004(2):1980-1987.
[11]	TEUNISSEN P J G. The least-squares ambiguity decorrelation adjustment: a method for fast GPS integer ambiguity estimation ［J］. Journal of Geodesy, 1995, 70(1-2): 65-82.
[12]	武志峰. 差异演化算法及其应用研究［D］. 北京交通大学, 2009.
[13]	汪慎文,丁立新,张文生, 等. 差分进化算法研究进展［J］. 武汉大学学报(理学版), 2014(4): 283-92.
[14]	BREST J, GREINER S, BOSKOVIC B, et al. Self-Adapting Control Parameters in Differential Evolution: A Comparative Study on Numerical Benchmark Problems ［J］. IEEE Transactions on Evolutionary Computation, 2006, 10(6): 646-657.
[15]	JONGE P D, TIBERIUS C. Integer Ambiguity Estimation with the Lambda Method ［M］. Springer Berlin Heidelberg, 1996.
[16]	TEUNISSEN P J G, JONGE P J D, TIBERIUS C C J M. The least-squares ambiguity decorrelation adjustment: its performance on short GPS baselines and short observation spans ［J］. Journal of Geodesy, 1997, 71(10): 589-602.
[17]	DE JONGE P J, TIBERIVS C C J M. The LAMBDA method for integer ambiguity estimation: Implementation aspects ［R］. Dekft Geodetic Computing Centre, Delft University of Technology, 1996.
[18]	XU P. Random simulation and GPS decorrelation ［J］. Journal of Geodesy, 2001, 75(7-8): 408-423.