Report icon

Report

False data injection in Kalman Filters in an aerospace setting; ADS-B data with simulated noise

Abstract:

Kalman Filters (KF) are recursive state estimation algorithms capable of combining and weighting deferent variables to estimate the real latent state of a system (Kalman, 1960). In this context, recursive reflects the property that not all previous data has to be kept in storage but every iteration incorporates information from previous observations and predictions (Maybeck, 1979). This made the KF widely applicable resulting in its implementation across various settings, including aerospace,...

Expand abstract
Publication status:
Not published
Peer review status:
Not peer reviewed

Actions


Access Document


Files:
  • (Author's original, x-pdf, 3.6MB)

Authors


More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
Journal:
CDT Technical Papers
Series:
CDT Technical Papers
Publication date:
2016-06-23
Keywords:
Pubs id:
pubs:652779
UUID:
uuid:23647ab8-d856-4f63-bdd2-c6a24391074b
Local pid:
pubs:652779
Deposit date:
2016-10-17

Terms of use


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP