基于蚁群算法的多面函数在GPS高程拟合中的应用

针对多面函数拟合法的中心节点难以选取的问题，提出将蚁群算法引入多面函数并结合稳健估计构建高精度拟合模型的方法。利用蚁群算法在复杂地形中快速寻找特征点，与少量非特征点共同作为中心节点参与模型构建，将稳健估计加入多面函数，运用选权迭代法剔除粗差对拟合模型的影响。GPS高程拟合数据处理实例表明，基于蚁群算法的多面函数结合稳健估计的拟合方法可有效剔除粗差的影响，且拟合精度比只用均匀格网法提高26%。

Application of Multi-Quadric Function Based on Ant Colony Algorithm in GPS Elevation Fitting

Aiming at the problem that the central node of the multi-quadric function fitting method is difficult to select, we introduce the method of the ant colony algorithm into the multi-quadric function and construct the high-precision fitting model with robust estimation.The ant colony algorithm is used to find feature points in complex terrain, and combines several non-feature points together as a central node in the construction model. Robustness is added to the multi-faceted function, and the effect of gross error on the fitting model is eliminated using the iterative method.GPS elevation fitting data processing example shows that the fitting method of multi-quadric function and robust estimation based on ant colony algorithm effectively eliminates the influence of gross error, fitting precision is improved by 26%.