Algorithm for the detection and isolation of systemic measurement errors in vision based/aided navigation systems

This paper introduces a new test statistic that can detect systematic errors in vision systems. This can be used for integrity monitoring of vision navigation systems. Current integrity monitoring methods look for agreement among the measurements from a camera. This method looks for agreement between separate cameras. If the measurements do not agree then a parameter of one of the cameras has changed resulting in a systematic error. An example of the usefulness of this test statistic is shown with a Monte Carlo test.