NDLI: Radar HRRP target recognition via statistics-based scattering centre set registration

Content Provider	IET Digital Library
Author	Wang, Jing jing Liu, Zheng Li, Tao Ran, Lei Xie, Rong
Abstract	Due to the presence of noise and range resolution variation, each attribute of the scattering centre (SC) extracted from high-resolution range profile (HRRP) data is a random variable fluctuating around the real attribute. For the scatterer-based target recognition method, the extraction error will disturb the similarity measurement between SC sets and adversely affect the recognition performance. In this study, a novel approach for HRRP target recognition is proposed via the statistics-based SC set registration. The attribute set of SCs is first characterised by a Gaussian mixture model (GMM) in which each Gaussian component represents the corresponding SC attributes containing the amplitude and position. Besides, the noise power and range resolution are taken into account into the GMM parameters, which enhances the recognition robustness against noise and resolution variation. Afterwards, based on the different stability of SC attributes against the variation of target-sensor orientation, the weighted Gaussian quadratic form distance is developed to register the test Gaussian mixture with the templates. The resulting recognition method considers the statistical property of the estimated attribute of the SC and exhibits robust recognition performance. Experiments conducted on the measured data demonstrate the validity and robustness of the proposed method.
Starting Page	1264
Ending Page	1271
Page Count	8
ISSN	17518784
Volume Number	13
e-ISSN	17518792
Issue Number	Issue 8, Aug (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rsn/13/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2018.5625
Journal	IET Radar, Sonar & Navigation
Publisher Date	2019-04-23
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Attribute Set Computer Vision And Image Processing Technique Corresponding SC Attributes Estimated Attribute Exhibits Robust Recognition Performance Extraction Error Feature Extraction Gaussian Component Gaussian Mixture Model Gaussian Processes GMM Parameter High-resolution Range Profile Data Image Recognition Noise Power Object Recognition Optical, Image And Video Signal Processing Radar HRRP Target Recognition Radar Resolution Radar Target Recognition Random Variable Fluctuating Range Resolution Variation Recognition Robustness Resulting Recognition Method SC Sets Scatterer-based Target Recognition Method Set Registration Similarity Measurement Statistical Property Statistics Statistics-based Scattering Centre Target-sensor Orientation Test Gaussian Mixture Weighted Gaussian Quadratic Form Distance
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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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
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