Paper
16 June 1997 Intelligent fusion processing in BMD applications
Claire L. McCullough, Katherine A. Byrd, Charles A. Bjork, Gary W. Grider, Bart Smith, Norman Morris, Belur V. Dasarathy
Author Affiliations +
Abstract
Intelligent processing techniques are applied to a ballistic missile defense (BMD) application, focused on classifying the objects in a typical threat complex, using fused IR and ladar sensors. These techniques indicate the potential to improve designation robustness against 'off-normal'/unexpected conditions, or when sensor data or classifier performance degrades. A fused sensor discrimination (FuSeD) simulation testbed was assembled for designation experiments, to evaluate test and simulation data, assess intelligent processor and classification algorithms, and evaluate sensor performance. Results were produced for a variety of neural net and other nonlinear classifiers, yielding high designation performance and low false alarm rates. Most classifiers yield a few percent in false alarm rate; rates are further improved when multiple techniques are applied vi a majority based fusion technique. Example signatures, features, classifier descriptions, intelligent controller design, and architecture are included. Work was performed for the discriminating interceptor technology program (DITP).
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Claire L. McCullough, Katherine A. Byrd, Charles A. Bjork, Gary W. Grider, Bart Smith, Norman Morris, and Belur V. Dasarathy "Intelligent fusion processing in BMD applications", Proc. SPIE 3067, Sensor Fusion: Architectures, Algorithms, and Applications, (16 June 1997); https://doi.org/10.1117/12.276118
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Cited by 3 scholarly publications.
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KEYWORDS
Sensors

LIDAR

Intelligent sensors

Neural networks

Data fusion

Doppler effect

Computer simulations

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