Does RAIM with Correct Exclusion Produce Unbiased Positions?
AbstractAs the navigation solution of exclusion-based RAIM follows from a combination of least-squares estimation and a statistically based exclusion-process, the computation of the integrity of the navigation solution has to take the propagated uncertainty of the combined estimation-testing procedure into account. In this contribution, we analyse, theoretically as well as empirically, the effect that this combination has on the first statistical moment, i.e., the mean, of the computed navigation solution. It will be shown, although statistical testing is intended to remove biases from the data, that biases will always remain under the alternative hypothesis, even when the correct alternative hypothesis is properly identified. The a posteriori exclusion of a biased satellite range from the position solution will therefore never remove the bias in the position solution completely. View Full-Text
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Teunissen, P.J.G.; Imparato, D.; Tiberius, C.C.J.M. Does RAIM with Correct Exclusion Produce Unbiased Positions? Sensors 2017, 17, 1508.
Teunissen PJG, Imparato D, Tiberius CCJM. Does RAIM with Correct Exclusion Produce Unbiased Positions? Sensors. 2017; 17(7):1508.Chicago/Turabian Style
Teunissen, Peter J.G.; Imparato, Davide; Tiberius, Christian C.J.M. 2017. "Does RAIM with Correct Exclusion Produce Unbiased Positions?" Sensors 17, no. 7: 1508.
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