Tracking a maneuvering target using sensors of variable quality

In an environment subject to sudden change, the accuracy of tracking and prediction is strongly influenced both by the sensor architecture and by the quality of the sensors. An image-enhanced algorithm is presented for both path following and covariance estimation in applications where the sensors a...

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 2000-04, Vol.36 (2), p.501-507
Main Authors: Boyd, J.E., Sworder, D.D.
Format: Article
Language:English
Subjects:
Acceleration
Aircraft components
Algorithms
Context modeling
Covariance
Difference equations
Differential equations
Electronic systems
Extended Kalman filter
Image sensors
Kinematics
Sensor systems
Sensors
Stochastic processes
Target tracking
Tracking
Trajectories
White noise
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Summary:In an environment subject to sudden change, the accuracy of tracking and prediction is strongly influenced both by the sensor architecture and by the quality of the sensors. An image-enhanced algorithm is presented for both path following and covariance estimation in applications where the sensors are subject to sudden and unpredictable variation in quality. For an illustrative trajectory, the performance of the algorithm is contrasted with an extended Kalman filter (EKF) and an image-enhanced algorithm based upon the nominal sensors.
ISSN:0018-9251
1557-9603
DOI:10.1109/7.845232