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Proceedings Paper

A Real Time (On Line) Adaptive Target Detection Technique For An Airborne Millimeter Wave Seeker Design
Author(s): A. B Mahmoodi; M. Kaveh
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Paper Abstract

An adaptive technique for detection of ground stationary targets in a variable clutter environment by an airborne millimeter wave radar is presented. The scheme consists of three basic units: an adaptive decorrelator, a clutter classifier, and a constant false alarm rate (CFAR) processor. Due to the inherent nature of radar returns (echoes), the signal consisting of target(S), clutter(C), and noise(N) are highly correlated. These signals are passed through a whitening matched filters combination. The selection of the parameters of whitening and matched filters is performed through an adaptive identification scheme (Kalman algorithm) using autoregressive(AR) and autoregressive-moving average(ARMA) models. The output of the matched filter is then passed through the pattern classifier unit, which determines whether the given clutter sample belongs to the Log-normal type or Weibull type statistical distribution families, and determines the appropriate detection threshold for the CFAR processor unit.

Paper Details

Date Published: 9 January 1984
PDF: 8 pages
Proc. SPIE 0424, Airborne Reconnaissance VII, (9 January 1984); doi: 10.1117/12.936200
Show Author Affiliations
A. B Mahmoodi, 3M Company (United States)
M. Kaveh, University of Minnesota (United States)

Published in SPIE Proceedings Vol. 0424:
Airborne Reconnaissance VII
Paul A. Henkel, Editor(s)

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