On-line multi-sensor registration for data fusion on airport surface

A block-processing methodology to dynamically estimate and cancel systematic multiple sensor errors is proposed and analyzed. Bias estimators are obtained from sequential consecutive blocks of measurement differences, achieving an accuracy equivalent to that reachable with an extended Kalman filter...

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 2007-01, Vol.43 (1), p.356-370
Main Authors: Garcia Herrero, J., Besada Portas, J.A., Casar Corredera, J.R.
Format: Article
Language:English
Subjects:
Accuracy
Airports
Algorithms
Calibration
Clocks
Computational efficiency
Computational modeling
Computer simulation
Data fusion
Deviation
Error detection
Information systems
Radar tracking
Sensor fusion
Sensor systems
Sensors
Surveillance
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Description
Summary:A block-processing methodology to dynamically estimate and cancel systematic multiple sensor errors is proposed and analyzed. Bias estimators are obtained from sequential consecutive blocks of measurement differences, achieving an accuracy equivalent to that reachable with an extended Kalman filter (EKF) operating over each pair, but with improved computational efficiency. The algorithm is formulated generically first and then applied to solve practical problems identified when fusing data on airport surfaces: global calibration, clock shift and local systematic deviations of sensor references. Performance, with significant improvement in tracking accuracy, is illustrated in simulated representative airport scenarios, fusing data from surface movement radar (SMR) and cooperative sensors
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2007.357139