Does RAIM with correct exclusion produce unbiased positions?

Does RAIM with correct exclusion produce unbiased positions?

Teunissen, P.J.G. (TU Delft Mathematical Geodesy and Positioning)
Imparato, D. (Curtin University)
Tiberius, C.C.J.M. (TU Delft Mathematical Geodesy and Positioning)

2017-07-01

As 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.

Best linear unbiased estimation (BLUE)
Bias
Correct detection (CD)
Correct identification (CI)
Global Navigation Satellite System (GNSS)
Level of significance
Missed detection (MD)
Receiver Autonomous Integrity Monitoring (RAIM)
Statistical hypothesis Testing

http://resolver.tudelft.nl/uuid:8d117940-3f17-4f07-83ee-b2a970ceb82d

https://doi.org/10.3390/s17071508

1424-8220

Sensors, 17 (7)

Institutional Repository

journal article

© 2017 P.J.G. Teunissen, D. Imparato, C.C.J.M. Tiberius