Scheduled System Maintenance:
On Monday, April 27th, IEEE Xplore will undergo scheduled maintenance from 1:00 PM - 3:00 PM ET (17:00 - 19:00 UTC). No interruption in service is anticipated.
By Topic

Ground moving target classification by using DCT coefficients extracted from micro-Doppler radar signatures and artificial neuron network

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 $13
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

4 Author(s)
Molchanov, P. ; Dept. of Signal Process., Tampere Univ. of Technol., Tampere, Finland ; Astola, J. ; Egiazarian, K. ; Totsky, A.

A novel approach to ground moving targets classification by using information features contained in micro-Doppler radar signatures is presented. Suggested approach is based on using discrete cosine transform (DCT) coefficients extracted from radar signature as a classification feature and multilayer perceptron (MLP) as a classifier. Proposed pattern classification algorithm was tested by utilizing experimental data measurements performed by ground surveillance Doppler radar system for four radar target classes as single moving human, groups of two and three moving persons and vegetation clutter. Suggested approach provides the probability of classification equal to 86%.

Published in:

Microwaves, Radar and Remote Sensing Symposium (MRRS), 2011

Date of Conference:

25-27 Aug. 2011