Iterative reweighted recursive least squares for robust positioning

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Abstract
A robust GPS positioning algorithm with high efficiency is presented to reduce the positioning error caused by the outlier. First, the robustness is obtained by the outlier-insensitive initial estimate. The robust initial estimate is selected from the separated group estimates under the stringent criterion. Secondly, the weights of the pseudo-ranges are calculated with the initial estimate. Finally, the efficiency of the initial estimate is improved by performing the iterative reweighted recursive least squares with the updated weights. Experimental data-processing results show that the proposed algorithm is effective to resist the outlier which has contaminated the high leverage observation.

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