Robust Estimation Method Based on Function Model of Successive Approximation
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Abstract In measurement practice, the residuals in least squares adjustment usually show various abnormal discrete distributions, including outliers, which is not conducive to the optimization of final measured values. Starting with the physical mechanism of dispersion and outlier of repeated observation errors, this paper puts forward the error correction idea of using the approximate function model of error to approach the actual function model of error step by step, gives a new theoretical method to optimize the final measured values, and proves the effectiveness of the algorithm by the ability of responding to the true values. This new idea is expected to be the ultimate answer of robust estimation theory.
2017 ◽
Vol 48
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pp. 209-216
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2021 ◽
Vol 32
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pp. 243-256
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2014 ◽
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pp. 2801-2805
1999 ◽
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2016 ◽
Vol 19
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pp. 182-187
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