| 参数带椭球约束平差算法的应用 |
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| 引用本文： | 肖兆兵,宋迎春,谢雪梅.参数带椭球约束平差算法的应用[J].大地测量与地球动力学,2018,38(9):964-967. |
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| 作者姓名： | 肖兆兵 宋迎春 谢雪梅 |
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| 摘 要： | 针对实际工程应用中遇到的参数带有范围约束的情形，提出带椭球约束的平差算法，并给出其具体模型和解算步骤。数值模拟实验和病态测边网数据计算表明，在处理病态问题时，最小二乘平差（least-squares，LS）已不适用，而与岭估计、奇异值分解法（singular value decomposition，SVD）以及不等式约束相比，本文算法精度更高。
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| 关 键 词： | 先验信息 病态问题 椭球约束 岭估计 奇异值分解 |
Application of Parameters with Ellipsoidal Constraints in Adjustment Algorithm |
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| XIAO Zhaobing,SONG Yingchun,XIE Xuemei.Application of Parameters with Ellipsoidal Constraints in Adjustment Algorithm[J].Journal of Geodesy and Geodynamics,2018,38(9):964-967. |
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| Authors: | XIAO Zhaobing SONG Yingchun XIE Xuemei |
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| Abstract: | This paper is aimed at parameters in the actual engineering application with territorial constraints, and proposes a new adjustment algorithm with ellipsoidal constraints, whose concrete model and solving steps are given. Results of simulated experimental data and morbid trilateration net data, show that the least-squares is not suitable for processing morbid problems. Compared with the results of ridge estimation, singular value decomposition (SVD) and inequality constraints, we show that the algorithm with ellipsoidal constraints of parameter has higher precision. |
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| Keywords: | prior information ill-posed problems ellipsoidal constraints ridge estimation singular value decomposition |
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