Publication

Innovation vs Residual KF Based GNSS/INS Autonomous Integrity Monitoring in Single Fault Scenario

Jan Skaloud
2017
Conference Papers

Abstract

We perform a comparison between an innovation and a residual based integrity monitoring in Extended Kalman Filters for the GNSS/INS hybridization. In this paper, we restrict the study to the detection of abrupt snapshot faults in order to get an intuitive insight. We study the differences in the distribution of the test statistics and the computation of the thresholds. We derive and compare the minimum detectable bias and we provide expressions for the protection levels for both approaches in the single fault situation. We compare them with the classical residual based GNSS RAIM algorithm. Additionally, we perform a sensitivity analysis of the integrity relevant parameters to the inertial sensor quality.

Official source

https://infoscience.epfl.ch/entities/publication/4a28bd03-f4bc-463a-9394-7e3974cc9fb7

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Jan Skaloud
2017
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/4a28bd03-f4bc-463a-9394-7e3974cc9fb7

About this result

Related concepts (23)

Statistics

Statistics (from German: Statistik, () "description of a state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal".

Test statistic

A test statistic is a statistic (a quantity derived from the sample) used in statistical hypothesis testing. A hypothesis test is typically specified in terms of a test statistic, considered as a numerical summary of a data-set that reduces the data to one value that can be used to perform the hypothesis test. In general, a test statistic is selected or defined in such a way as to quantify, within observed data, behaviours that would distinguish the null from the alternative hypothesis, where such an alternative is prescribed, or that would characterize the null hypothesis if there is no explicitly stated alternative hypothesis.

Kalman filter

For statistics and control theory, Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, including statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe. The filter is named after Rudolf E. Kálmán, who was one of the primary developers of its theory.