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Monterey, CA; Naval Postgraduate School

Ballistic missile tracking using the interacting multiple model joint probabilistic data association filter

Abstract

dc:description.abstract

The success of interceptors used by the United States ballistic missile defense program is jeopardized by the use of hostile missile decoy deployment and evasive maneuvers. The ability to discriminate between legitimate threats and decoys is a crucial requirement for interceptor algorithms. The feasibility of the interacting multiple model joint probabilistic data association filter to effectively track a ballistic missile and detect decoys and maneuvers is the focus of this thesis. Model development and data association schemes are discussed along with optimized values for selected parameters. Performance comparisons of the resultant algorithm to a standard Kalman filter utilizing a nearest neighbor discriminator are conducted. Scenarios include combinations of missile maneuver and decoy deployment. While the Kalman filter experiences limited success, the proposed filter tracks the missile in every scenario.

Degree

thesis:*
Department dc:contributor.department
Electrical and Computer Engineering (ECE)
Grantor dc:publisher
Monterey, CA; Naval Postgraduate School
Year dc:date.issued
2013

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Dunton, Timothy M.
Advisor dc:contributor.advisor
  • Hutchins, Robert G.

Rights

dc:rights
Statement dc:rights
  • This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/10945/37618
OAI identifier oai:identifier
oai:calhoun.nps.edu:10945/37618

Chain of custody

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Naval Postgraduate School
Base URL
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Last updated
2026-07-27
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citation

Dunton, Timothy M.. Ballistic missile tracking using the interacting multiple model joint probabilistic data association filter. Monterey, CA; Naval Postgraduate School, 2013. https://hdl.handle.net/10945/37618