Application of Three-Dimensional Filtering to Moving Target Detection

The standard approach to the detection of a stationary target immersed within an optically observed scene is to use integration to separate the target energy from the background clutter. When the target is nonstationary and moves with fixed velocity relative to the clutter, the procedure for integra...

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 1983-11, Vol.AES-19 (6), p.898-905
Main Authors: Reed, I.S., Gagliardi, R.M., Shao, H.m.
Format: Article
Language:English
Subjects:
Applied sciences
Array signal processing
Exact sciences and technology
Filtering theory
Integrated optics
Layout
Object detection
Optical design
Optical detectors
Optical filters
Radiolocalization and radionavigation
Target tracking
Telecommunications
Telecommunications and information theory
Very large scale integration
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Summary:The standard approach to the detection of a stationary target immersed within an optically observed scene is to use integration to separate the target energy from the background clutter. When the target is nonstationary and moves with fixed velocity relative to the clutter, the procedure for integrating the target signal is no longer obvious. In this paper it is shown that the problem of tracking a target having a fixed velocity can be cast into a general framework of three-dimensional filter theory. From this point of view, the target detection problem reduces to the problem of finding optimal three-dimensional filters in the three-dimensional transform domain and processing the observed scene via this filtering. The design of these filters is presented, taking into account the target, clutter, and optical detection models. Performance is computed for a basic clutter model, showing the effective increase in detectability as a function of the target velocity. The three-dimensional transform approach is readily compatible with VLSI array processing technology.
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.1983.309401