Sensor fusion for boost phase interception of ballistic missiles
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Authors
Humali, I. Gokhan
Subjects
Advisors
Pace, Phillip E.
Tummala, Murali
Date of Issue
2006-09
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
In the boost phase interception of ballistic missiles, determining the exact position of a ballistic missile has a significant importance. Several sensors are used to detect and track the missile. These sensors differ from each other in many different aspects. The outputs of radars give range, elevation and azimuth information of the target while space based infrared sensors give elevation and azimuth information. These outputs have to be combined (fused) achieve better position information for the missile. The architecture that is used in this thesis is decision level fusion architecture. This thesis examines four algorithms to fuse the results of radar sensors and space based infrared sensors. An averaging technique, a weighted averaging technique, a Kalman filtering approach and a Bayesian technique are compared. The ballistic missile boost phase segment and the sensors are modeled in MATLAB. The missile vector and dynamics are based upon Newton's laws and the simulation uses an earth-centered coordinate system. The Bayesian algorithm has the best performance resulting in a rms missile position error of less than 20 m.
Type
Thesis
Description
Series/Report No
Organization
Graduate School of Engineering and Applied Science (GSEAS)
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
Format
xiv, 75 p. : ill. (some col.) ;
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
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Copyright is reserved by the copyright owner.