DocumentCode
2790813
Title
Online sensor registration
Author
Vermaak, Jaco ; Maskell, Simon ; Briers, Mark
Author_Institution
Dept. of Eng., Cambridge Univ.
fYear
2005
fDate
5-12 March 2005
Firstpage
2117
Lastpage
2125
Abstract
In a multi-sensor scenario, accurate data fusion is best achieved by processing the measurements from all the sensors at a fusion node to produce tracks. However, inaccuracies in the position and/or rotation of the sensor can lead to "ghost" tracks, particularly when the sensors are not co-located. This paper presents a framework which models the uncertainty over the sensors\´ registration parameter (e.g. position and rotation) and discloses an unscented implementation technique (other methods based on particle filters can be accommodated within our framework), where each sensor self-localises using targets of opportunity. The aim is to solve the sensor registration problem whilst adding minimal overhead to an existing tracker, which is facilitated by making the standard assumption that the state of the joint target factorises over the individual targets
Keywords
particle filtering (numerical methods); sensor fusion; target tracking; uncertainty handling; data fusion; ghost tracks; online sensor registration; particle filters; sensor self-localisation; unscented implementation; Cams; Data engineering; Electrical capacitance tomography; Noise measurement; Notice of Violation; Remotely operated vehicles; Sensor fusion; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Aerospace Conference, 2005 IEEE
Conference_Location
Big Sky, MT
Print_ISBN
0-7803-8870-4
Type
conf
DOI
10.1109/AERO.2005.1559503
Filename
1559503
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