Does RAIM with correct exclusion produce unbiased positions?

Research output: Contribution to journalArticleScientificpeer-review

13 Citations (Scopus)
267 Downloads (Pure)


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.
Original languageEnglish
Article number1508
Number of pages16
Issue number7
Publication statusPublished - 1 Jul 2017


  • 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


Dive into the research topics of 'Does RAIM with correct exclusion produce unbiased positions?'. Together they form a unique fingerprint.

Cite this