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Franz J. Polster - Abstract |
Datenfusion - Begriffsbestimmung und Techniken
Data Fusion - Definition and Techniques
Franz J. Polster
Source: Presentation AFCEA Chapter München, Feb 3, 1998
Abstract:
The notion of Data Fusion (DF) refers to any process of intelligently combining data
from multiple sensors to derive meaningful information not available from any individual
sensor.
Military applications of DF include a wide range of command, communication and
intelligence missions for both tactical and strategic warfare.
In an attempt to capture this diversity of DF a comprehensive - and thus necessarily
generic - definition was proposed by JDL DFS, which describes DF as
a "multilevel, multifaceted process dealing with the detection , association,
correlation, estimation and combination of data and information from multiple sources
to achieve refined state and identity estimation, and complete and timely assessments of
situation and threat".
In order to illustrate the extent and diversity of DF three application areas for DF are presented and discussed: (1) antisubmarine warfare, (2) offensive-defensive tactical warfare, (3) land battle. In this context also factors providing the motivation for developing automated DF systems are addressed.
A generalized processing model, also developed by JDL DFS, is discussed, which
identifies three levels of fusion processing results:
position and identity estimates (level 1),
situation assessments (level 2), threat assessments (level 3).
The sub-tasks of the command-control cycle to be supported by automated DF systems
are pointed out, a generic system architecture is delineated
consisting of components "sensors", "DF functions",
"decision support functions", "human control/command".
Four generic DF processes, which in general relate to and depend on each other, are identified: "classification", "correlation", "aggregation" and "fusion". Automated DF systems draw on techniques from a diversity of disciplines: