NDLI: Learning using privileged information for HRRP-based radar target recognition

Content Provider	IET Digital Library
Author	Guo, Yu Xiao, Huaitie Kan, Yingzhi Fu, Qiang
Abstract	A novel machine learning method named extended support vector data description with negative examples (ESVDD-neg) is developed to classify the fast Fourier transform-magnitude feature of complex high-resolution range profile (HRRP), motivated by the problem of radar automatic target recognition. The proposed method not only inherits the close non-linear boundary advantage of support vector data description with negative examples model but also incorporates a new learning paradigm named learning using privileged information into the model. It leads to the appealing application with no assumptions regarding the distribution of data and needs less training samples and prior information. Besides, the second order central moment is selected as privileged information for better recognition performance, weakening the effect of translation sensitivity, and the normalisation contributes to eliminating the amplitude sensitivity. Hence, there will be a remarkable improvement of recognition accuracy not only with small training dataset but also under the condition of low signal-to-noise ratio. Numerical experiments based on two publicly UCI datasets and HRRPs of four aircrafts demonstrate the feasibility and superiority of the proposed method. The noise robust ESVDD-neg is ideal for HRRP-based radar target recognition.
Starting Page	188
Ending Page	197
Page Count	10
ISSN	17519675
Volume Number	12
e-ISSN	17519683
Issue Number	Issue 2, Apr (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/12/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2016.0625
Journal	IET Signal Processing
Publisher Date	2017-09-15
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Close Nonlinear Boundary Advantage Complex High-resolution Range Profile Digital Signal Processing Electrical Engineering Computing ESVDD-neg Extended Support Vector Data Description-with-negative Examples Fast Fourier Transform Fast Fourier Transform-magnitude Feature Classification HRRP-based Radar Target Recognition Integral Transforms in Numerical Analysis Knowledge Engineering Technique Learning in AI Learning Paradigm Low Signal-to-noise Ratio Machine Learning Method Radar Automatic Target Recognition Problem Radar Computing Radar Equipment Radar Signal Processing Radar Target Recognition Signal Classification Signal Processing And Detection System And Application Translation Sensitivity UCI Datasets
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

HRRP classification based on multi-scale fusion sparsity preserving projections

Deep forest for radar HRRP recognition

Robust sequential high-resolution range profile recognition based on the infinite conditional restricted Boltzmann machine

Radar recognition of multiple micro-drones based on their micro-Doppler signatures via dictionary learning

Radar HRRP target recognition based on stacked denosing sparse autoencoder

Motion classification for radar moving target via STFT and convolution neural network

Radar HRRP target recognition in frequency domain based on autoregressive model

Radar HRRP recognition based on CNN

Synthetic aperture radar target recognition of incomplete training datasets via Siamese network

Learning using privileged information for HRRP-based radar target recognition

Similar Documents

HRRP classification based on multi-scale fusion sparsity preserving projections

Deep forest for radar HRRP recognition

Robust sequential high-resolution range profile recognition based on the infinite conditional restricted Boltzmann machine

Radar recognition of multiple micro-drones based on their micro-Doppler signatures via dictionary learning

Radar HRRP target recognition based on stacked denosing sparse autoencoder

Motion classification for radar moving target via STFT and convolution neural network

Radar HRRP target recognition in frequency domain based on autoregressive model

Radar HRRP recognition based on CNN

Synthetic aperture radar target recognition of incomplete training datasets via Siamese network

Learning using privileged information for HRRP-based radar target recognition