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An Algorithm for Circle Curve Fitting Based on the Constrained Least Square Model Represented by Mosaic Observation Points

机译:一种基于马赛克观测点代表的约束最小二乘模型的圆曲线拟合算法

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In the application of engineering technology, a certain number of disturbed observation points with errors are often used to fit a plane circle. Considering the distribution characteristics of these points, two kinds of models are presented in this paper: an unconstrained non-linear least square model and a non-linear least square model constrained by the mosaic center coordinates for the plane circle fitting. The lsqnonlin function for nonlinear least square algorithm is applied to work out the unconstrained least square model. The searching method is adopted to figure out the constrained model by analyzing the symmetry of simulated data, determining the initial value for searching and simplifying the solving process. By contrasting the two fitting results, it is obvious that the constrained least square model can successfully simplify the computation with higher accuracy. Furthermore, this algorithm can also be used for the computation of spherical centers and radii in the three-dimensional space.
机译:在工程技术的应用中,通常使用具有误差的一定数量的扰乱观察点来适应平面圆。考虑到这些点的分布特性,本文提出了两种模型:由镶嵌圆形配件的马赛克中心坐标约束的不受约束的非线性最小二乘模型和非线性最小二乘模型。非线性最小二乘算法的LSQNONLIN函数应用于计算出不受约束最小二乘模型。采用搜索方法来通过分析模拟数据的对称性来弄清楚模型,确定搜索和简化求解过程的初始值。通过对比两个拟合结果,很明显,约束最小二乘模型可以以更高的精度成功简化计算。此外,该算法还可以用于三维空间中的球面中心和半径的计算。

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