部分有界不确定性数据平差方法

Adjustment of Part Bounded Uncertain Data

针对传统最小二乘法以及总体最小二乘法不完全适合于系数矩阵带有有界误差,及有界不确定性数据平差方法也不能直接用于系数矩阵只是部分带有有界误差的问题,基于有界误差问题的平差方法,给出解决部分有界问题的迭代算法,并验证该方法的有效性。

Neither least-squares nor total least-squares can be applied to the condition that a coefficient matrix has bounded errors very well.In addition,the adjustment of bounded uncertain data cannot be directly applied in this condition.Therefore,the part bounded problem is analyzed in this paper.An iterative algorithm to solve this issue is proposed based on the adjustment of bounded uncertain data.The validity of this method is proved through an example.