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Proceedings Paper

Neural network based moving target indicator for radar applications
Author(s): Farid Amoozegar
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Paper Abstract

Although techniques of radar signal processing, including the moving target indicator (MTI), have been vastly improved by the availability of digital computers in recent years, these methods are generally based on complex mathematical procedures which make the engineering and design of radar receivers rather costly and vulnerable to electronic faults. On the other hand, biological systems (e.g., insects, birds) have capabilities far beyond those of the conventional MTI processors. This paper provides some evidence that Doppler shifts can easily be extracted with neural networks even in situations where only a limited number of noisy pulses are available for processing. Furthermore, it is easier to shape the frequency response of the neural network-based MTI (NN-MTI) as desired without needing the complex process of pole placement, which is traditionally required in both digital and analog filter design procedures. The nonlinear processing capability of a neural network is utilized to efficiently combine the Doppler processing and integration performed by conventional MTI and its coprocessor (i.e., integrator). The MTI implementation with neural networks reduces the number of required independent pulses for Doppler shift extraction in the presence of clutter. There are several other conflicting requirements for the optimum MTI design where the algorithmic procedures may not be as efficient. Therefore, shaping the magnitude frequency response of MTI filters demands the flexibilities offered by neural networks.

Paper Details

Date Published: 6 April 1995
PDF: 11 pages
Proc. SPIE 2492, Applications and Science of Artificial Neural Networks, (6 April 1995); doi: 10.1117/12.205206
Show Author Affiliations
Farid Amoozegar, Univ. of Arizona (United States)

Published in SPIE Proceedings Vol. 2492:
Applications and Science of Artificial Neural Networks
Steven K. Rogers; Dennis W. Ruck, Editor(s)

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