引用本文: 孙振, 曲国庆, 苏晓庆, 杜存鹏, 邓晓景. 测距定位方程参数估计的Frozen-Barycentre算法[J]. 武汉大学学报 ( 信息科学版), 2020, 45(9): 1478-1484.
SUN Zhen, QU Guoqing, SU Xiaoqing, DU Cunpeng, DENG Xiaojing. Frozen-Barycentre Algorithm for Solving Distance Equations[J]. Geomatics and Information Science of Wuhan University, 2020, 45(9): 1478-1484.
 Citation: SUN Zhen, QU Guoqing, SU Xiaoqing, DU Cunpeng, DENG Xiaojing. Frozen-Barycentre Algorithm for Solving Distance Equations[J]. Geomatics and Information Science of Wuhan University, 2020, 45(9): 1478-1484.

## Frozen-Barycentre Algorithm for Solving Distance Equations

• 摘要: 针对传统病态非线性最小二乘求解不稳定且可靠性低的特点, 基于测距定位方程最小二乘解性质, 提出了一种Frozen-Barycentre迭代法。该方法将萨玛斯基应用于重心迭代法, 实现了内迭代和外迭代的转换, 通过减少导数计算量节省运算时间, 提高重心迭代法的收敛效率。并采用模拟数据和水下定位实测数据, 验证了该方法的数值收敛解优于线性化平差估计解, 收敛效率优于重心迭代法。

Abstract: For unstablity and unreliability of the traditional nonlinear least squares solution of ill-conditioned problems, a Frozen-Barycentre iterative algorithm is proposed based on the least squares solution property of nonlinear ranging location. The method applies the Samaski technique to Barycentre iterative method, to realize the transformation of internal and external iterations. This algorithm improves the convergence efficiency of Barycentre iterative method by reducing the derivative calculation. And the numerical convergence experiments of the method are performed. The results show that the numerical precision of proposed method is better than that of the linearized adjustment estimation, and the convergence property is more efficient than the Barycentre iterative method.

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