一种基于蚁群算法的山区GPS高程异常拟合方法  

A GPS Height Anomaly Fitting Method in Mountainous Area Based on Ant Colony Algorithm

作　　者：蒲伦 唐诗华 张紫萍 李宗婉 张炎 PU Lun;TANG Shihua;ZHANG Ziping;LI Zongwan;ZHANG Yan(College of Geomaties and Geoinformation,Guilin University of Technology,Guilin 541006,China;Guangxi Key Laboratory of Spatial Information and Geomatics,Guilin 541006,China;Qinghai Eeologieal Enviromnent Remote Sensing Monitoring Center,Xining 810007,China)

机构地区：[1]桂林理工大学测绘地理信息学院,广西桂林541006 [2]广西空间信息与测绘重点实验室,广西桂林541006 [3]青海省生态环境遥感监测中心,青海西宁810007

出　　处：《测绘通报》2018年第8期26-31,共6页Bulletin of Surveying and Mapping

基　　金：国家自然科学基金(41571328);广西空间信息与测绘重点实验室基金(桂科能15-140-07-05;桂科能16-380-25-13)

摘　　要：针对在山区地形条件复杂情况下构建GPS高程异常拟合模型精度难以满足需求的问题,将蚁群算法与多面函数法进行了融合。采用蚁群算法获取部分特征点,充分发挥特征点的表述作用,构建了更高精度的拟合模型。通过算例分析可知,融合方法求得研究区域内拟合点的内符合精度为2.5 mm,检核点的总体精度为4.4 mm,内外符合精度均高于常规拟合模型的精度。结果表明,基于蚁群算法的山区GPS高程异常拟合方法有效可行,同时证明了蚁群算法寻找最优特征点具有一定的优势,对于建模研究具有很好的参考价值。In order to solve the problem that the accuracy of GPS elevation anomaly fitting model can＇t meet the accuracy demand in the complicated terrain conditions in mountainous areas,the ant colony algorithm combined with the multi-surface function method is proposed.Some feature points are got by using ant colony algorithm and the expression of feature points are elaborated to build a more accurate fitting model.Through analysis of the example,it can be seen that the in-accuracy of the fit points in the study area is 2.5 mm,the overall accuracy of the checkpoints is 4.4 mm,and the accuracy of inside and outside matches is higher than that of the conventional fitting model.The results show that the method of GPS elevation anomaly fitting based on ant colony algorithm was feasible and effective.At the same time,it proves that ant colony algorithm has certain advantages in finding the optimal feature point,which has a good reference value for modeling research.

关 键 词：GPS高程异常 蚁群算法 参数寻优 均匀格网 精度分析 

分 类 号：P228.4[天文地球—大地测量学与测量工程]