Pulse doppler radar target recognition using a two-stage SVM procedure

Date

2010-07-07

Authors

Eryildirim, A.
Onaran, I.

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Source Title

IEEE Transactions on Aerospace and Electronic Systems

Print ISSN

0018-9251

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Publisher

IEEE

Volume

47

Issue

2

Pages

1450 - 1457

Language

English

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Abstract

It is possible to detect and classify moving and stationary targets using ground surveillance pulse-Doppler radars (PDRs). A two-stage support vector machine (SVM) based target classification scheme is described here. The first stage tries to estimate the most descriptive temporal segment of the radar echo signal and the target signal is classified using the selected temporal segment in the second stage. Mel-frequency cepstral coefficients of radar echo signals are used as feature vectors in both stages. The proposed system is compared with the covariance and Gaussian mixture model (GMM) based classifiers. The effects of the window duration and number of feature parameters over classification performance are also investigated. Experimental results are presented.

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