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On the errors-in-variables model with inequality constraints of dependent variables for geodetic transformation

机译:大地变换中因变量不等式约束的变量误差模型

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摘要

The Total least-squares (TLS) adjustment with inequality constraints has received increased attention in geodesy over the last three years. In the most recent work, inequality constraints have been presented that can restrict unknown parameters and independent variables, but no one has provided an inequality-constrained adjustment for restricting dependent variables. In this work, we review the TLS adjustment methods in terms of different model formulations and then investigate the errors-in-variables model with inequality constraints for dependent variables. Finally, we demonstrate the practicality of our approach with a planar geodetic transformation, where the uncertainty of the target observations is reduced via the inequality constraints for dependent variables.
机译:在过去三年中,具有不等式约束的总最小二乘(TLS)调整在大地测量学中受到越来越多的关注。在最近的工作中,提出了不平等约束条件,可以限制未知参数和自变量,但是没有人提供不平等约束条件的调整来限制因变量。在这项工作中,我们根据不同的模型公式回顾了TLS调整方法,然后研究了对因变量具有不等式约束的变量误差模型。最后,我们通过平面大地测量论证了我们方法的实用性,其中通过因变量的不等式约束来减少目标观测值的不确定性。

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