A new fusion architecture is presented and some preliminary results on field data are shown. The architecture consists of a new de- cision level fusion algorithm, the piecewise level fusion algorithm (PLFA), integrated with an expert system based user assistant. The PLFA tech- nique extends a known two class fusion decision level detection tech- nique to a multiple class fusion classifier technique. The expert system assistant calculates the parameters necessary to automatically adapt the PLFA to the required performance. An interactive integration of the PLFA module with the expert system module allows for effective search for fusion parameters while shielding the user from the mathematical com- plexity of the fusion procedure. This integration enables the detection of deadlocks and the generation of guidance to the user in parameter se- lection. The overall architecture and processing required to develop the current system from a man-in-the-loop system to a fully automated fu- sion system are also described. © 1998 Society of Photo-Optical Instrumentation Engineers. (S0091-3286(98)01802-9)
[1]
Mongi A. Abidi,et al.
Data fusion in robotics and machine intelligence
,
1992
.
[2]
Claire L. McCullough,et al.
Multilevel fusion exploitation
,
1996,
Defense, Security, and Sensing.
[3]
Ramanarayanan Viswanathan,et al.
Optimal Decision Fusion in Multiple Sensor Systems
,
1987,
IEEE Transactions on Aerospace and Electronic Systems.
[4]
George A. Lampropoulos,et al.
E-O and SAR image analysis and registration applications
,
1997,
Defense, Security, and Sensing.
[5]
Jake K. Aggarwal,et al.
Multisensor Fusion for Computer Vision
,
1993,
NATO ASI Series.
[6]
Richard T. Antony,et al.
Principles of Data Fusion Automation
,
1995
.
[7]
Pierre Valin,et al.
Fusion of imaging and nonimaging data for surveillance aircraft
,
1997,
Defense, Security, and Sensing.
[8]
James Llinas,et al.
An introduction to multisensor data fusion
,
1997,
Proc. IEEE.