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SUMMARY:Safe and accurate satellite navigation with non-Gaussian models - 
 Dr Ian Sheret - Polymath Insight Limited
DTSTART:20220504T140500Z
DTEND:20220504T145500Z
UID:TALK172958@talks.cam.ac.uk
CONTACT:Ben Karniely
DESCRIPTION:Global navigation satellite systems (GNSS) are a very well est
 ablished technology\, which provides a rich and flexible framework for man
 y different positioning applications. The most familiar uses are standard 
 positioning applications which usually provides accuracy of a few meters\,
  but can sometimes give very wrong answers. With some care and extra exter
 nal resources\, GNSS can also provide very high accuracy (centimetre scale
 ) positioning by exploiting carrier phase measurements. In other cases (e.
 g. aircraft landing systems) we need safety critical GNSS systems\; in pra
 ctice this is done by ignoring carrier phase observations\, and using high
 ly conservative inference frameworks which sacrifice accuracy in return fo
 r safety. For self-driving vehicle applications\, none of these existing s
 ystems are really suitable: we want both accuracy and safety\, but convent
 ional approaches can not deliver both at the same time.\n\nIn this talk\, 
 I argue that non-Gaussian error models are the key ingredient needed to bu
 ild future GNSS systems which can be both safe and accurate. Although cons
 iderable care and insight is needed to use these models\, the pay-off is a
  system which can exploit the high accuracy of carrier phase observations\
 , without introducing false assumptions which can lead to unsafe performan
 ce. I also show the practical engineering steps needed to overcome the for
 midable computational challenge this approach brings when applied to a rea
 l-time system.\n\nLink to join virtually: https://cl-cam-ac-uk.zoom.us/j/9
 7767639783?pwd=T09GcVJxZUNEUFEvRnZnbWwxeEwzQT09\n\nA recording of this tal
 k is available at the following link: https://www.cl.cam.ac.uk/seminars/we
 dnesday/video/
LOCATION:Lecture Theatre 1\, Computer Laboratory\, William Gates Building
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