Paper
28 July 1997 Approach to multisensor/multilook information fusion
Harley R. Myler, Ronald Patton
Author Affiliations +
Abstract
We are developing a multi-sensor, multi-look Artificial Intelligence Enhanced Information Processor (AIEIP) that combines classification elements of geometric hashing, neural networks and evolutionary algorithms in a synergistic combination. The fusion is coordinated using a piecewise level fusion algorithm that operates on probability data from statistics of the individual classifiers. Further, the AIEIP incorporates a knowledge-based system to aid a user in evaluating target data dynamically. The AIEIP is intended as a semi-autonomous system that not only fuses information from electronic data sources, but also has the capability to include human input derived from battlefield awareness and intelligence sources. The system would be useful in either advanced reconnaissance information fusion tasks where multiple fixed sensors and human observer inputs must be combined or for a dynamic fusion scenario incorporating an unmanned vehicle swarm with dynamic, multiple sensor data inputs. This paper represents our initial results from experiments and data analysis using the individual components of the AIEIP on FLIR target sets of ground vehicles.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Harley R. Myler and Ronald Patton "Approach to multisensor/multilook information fusion", Proc. SPIE 3068, Signal Processing, Sensor Fusion, and Target Recognition VI, (28 July 1997); https://doi.org/10.1117/12.280787
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Cited by 1 scholarly publication.
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KEYWORDS
Sensors

Evolutionary algorithms

Data fusion

Neural networks

Detection and tracking algorithms

Information fusion

Data processing

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