Robust airborne target recognition based on recurrence plot quantification of micro-Doppler radar signatures

A robust target recognition method proposed based on recurrence plot and recurrence quantification analysis (RQA) to generate robust features against noise, target velocity and aspect angle from micro-Doppler (m-D) signatures. The proposed method is tested on simulated data of three different target...

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Bibliographic Details
Published in2016 17th International Radar Symposium (IRS) pp. 1 - 4
Main Authors Johari, Mohammad Mahdi, Nayebi, Mohammad Mahdi
Format Conference Proceeding Journal Article
LanguageEnglish
Published IEEE 21.06.2016
Subjects
Airborne radar
Classification
Coherence
Indexes
low resolution
Matrix decomposition
multiclass support vector machine
Noise
Radar
Radar signatures
recurrence plot
recurrence quantification analysis
Robustness
Simulation
Spectrogram
Support vector machines
Target recognition
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Summary:A robust target recognition method proposed based on recurrence plot and recurrence quantification analysis (RQA) to generate robust features against noise, target velocity and aspect angle from micro-Doppler (m-D) signatures. The proposed method is tested on simulated data of three different targets using multiclass support vector machine (MSVM) and classification rate of about 95 % is achieved. Also, effect of noise and coherent processing time (CPT) on classification rate is investigated.
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SourceType-Conference Papers & Proceedings-2
ISSN:2155-5753
DOI:10.1109/IRS.2016.7497362