By Topic

Experimental analysis of an innovations-based detection algorithm for surveillance radar

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Metford, P.A.S. ; McMaster University, Communications Research Laboratory, Hamilton, Canada ; Haykin, S.

A very rapidly convergent solution (in the form of a likelihood ratio test) for the problem of detecting a discrete-time stochastic process in additive white Gaussian noise has been derived. This likelihood ratio test is applied to the problem of moving-target detection as encountered in an airport-surveillance radar system. Using real radar data, the receiver operating characteristics are obtained for two different implementations of this adaptive detection algorithm, and for the three generations of the classical moving-target-detection algorithm presently in use in modern radar systems. The best of the two implementations of the adaptive detection algorithm employs Kalman prediction tapped delay-line filters and attains a minimum of 3 dB average performance improvement relative to the classical moving-targer-detection algorithms.

Published in:

Communications, Radar and Signal Processing, IEE Proceedings F  (Volume:132 ,  Issue: 1 )