A Pattern Recognition Approach to Threat Stabilization

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Authors
  1. Allouche, M.K.
Corporate Authors
Defence R&D Canada - Valcartier, Valcartier QUE (CAN)
Abstract
Threat evaluation is of great importance in the command and control decision making process. Due to highly dynamic changes in the environment, it becomes more and more difficult to assign a stable threat value to an entity. This work aims at stabilizing the threat value assigned to a moving entity having a maneuvering behaviour. To this end, a special type of neural networks, the Self Organizing Maps, is used in order to extract some important features from the kinematics of the moving entity. The direction of advance of such an entity is computed based on the extracted features. The stabilization of such a direction of advance allows the stabilization of the threat value assigned to such an entity, especially when this value is based on the closest point of approach concept. The proposed approach is tested over a simulated data set and compared with other stabilization approaches such as the Least-Squares Regression Line method.

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Report Number
DRDC-VALCARTIER-TR-2002-239 — Technical Report
Date of publication
01 Jun 2006
Number of Pages
50
DSTKIM No
CA027404
CANDIS No
525499
Format(s):
CD ROM

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