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Proceedings Paper

Geospatial feature based automatic target recognition (ATR) using data models
Author(s): Holger Jaenisch; James Handley; Nathaniel Albritton; John Koegler; Steven Murray; Willie Maddox; Stephen Moren; Tom Alexander; William Fieselman; Robert Caspers
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Paper Abstract

We present a method for deriving an automatic target recognition (ATR) system using geospatial features and a Data Model populated decision architecture in the form of a self-organizing knowledge base. The goal is to derive an ATR that recognizes targets it has seen before while minimizing false alarms (zero false alarms). We present an investigation of the performance of analytical Data Models as a sensor and data fusion process for automatic target recognition (ATR), and summarize results including on a 2 km background run where no false alarms were encountered.

Paper Details

Date Published: 27 April 2010
PDF: 12 pages
Proc. SPIE 7697, Signal Processing, Sensor Fusion, and Target Recognition XIX, 76971B (27 April 2010); doi: 10.1117/12.863705
Show Author Affiliations
Holger Jaenisch, Licht Strahl Engineering Inc (United States)
The Johns Hopkins Univ. (United States)
James Handley, Amtec Corp. (United States)
Nathaniel Albritton, Amtec Corp. (United States)
John Koegler, Amtec Corp. (United States)
Steven Murray, Amtec Corp. (United States)
Willie Maddox, Amtec Corp. (United States)
Stephen Moren, Amtec Corp. (United States)
Tom Alexander, Amtec Corp. (United States)
William Fieselman, Amtec Corp. (United States)
Robert Caspers, Amtec Corp. (United States)

Published in SPIE Proceedings Vol. 7697:
Signal Processing, Sensor Fusion, and Target Recognition XIX
Ivan Kadar, Editor(s)

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