Target Recognition Using Linear Classification of High Range Resolution Radar Profiles PDF Download
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Author: Ricardo A. Diaz
Publisher:
ISBN: 9781423519942
Category : Pattern recognition systems
Languages : en
Pages : 111
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Book Description
High Range Resolution (HRR) radar profiles map three-dimensional target characteristics onto one-dimensional signals that represent reflected radar intensity along target extent. In this thesis, second through fourth statistical moments are extracted from HRR profiles and input to Fisher Linear Discriminant (FLD) classifiers. An iterative classification process is applied that gradually minimizes required a priori knowledge about the target data. It is found that the second through fourth statistical moments of HRR profiles are useful features in the FLD classification of dissimilar targets and they provide reasonable discrimination of similar targets. Greater than 69% correct classification for two-target scenarios and greater than 60% correct classification for three-target scenarios is obtained using a single HRR profile extracted from a full 360-degree aspect angle window. A key contribution of this thesis is the demonstration that simple statistical moment features and simple linear classifiers can be used to effectively classify HRR profiles.
Author: Ricardo A. Diaz
Publisher:
ISBN: 9781423519942
Category : Pattern recognition systems
Languages : en
Pages : 111
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Book Description
High Range Resolution (HRR) radar profiles map three-dimensional target characteristics onto one-dimensional signals that represent reflected radar intensity along target extent. In this thesis, second through fourth statistical moments are extracted from HRR profiles and input to Fisher Linear Discriminant (FLD) classifiers. An iterative classification process is applied that gradually minimizes required a priori knowledge about the target data. It is found that the second through fourth statistical moments of HRR profiles are useful features in the FLD classification of dissimilar targets and they provide reasonable discrimination of similar targets. Greater than 69% correct classification for two-target scenarios and greater than 60% correct classification for three-target scenarios is obtained using a single HRR profile extracted from a full 360-degree aspect angle window. A key contribution of this thesis is the demonstration that simple statistical moment features and simple linear classifiers can be used to effectively classify HRR profiles.
Author: Steven P. Jacobs
Publisher:
ISBN:
Category :
Languages : en
Pages : 290
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Book Description
Author: Uttam K. Majumder
Publisher: Artech House
ISBN: 1630816396
Category : Technology & Engineering
Languages : en
Pages : 290
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Book Description
This authoritative resource presents a comprehensive illustration of modern Artificial Intelligence / Machine Learning (AI/ML) technology for radio frequency (RF) data exploitation. It identifies technical challenges, benefits, and directions of deep learning (DL) based object classification using radar data, including synthetic aperture radar (SAR) and high range resolution (HRR) radar. The performance of AI/ML algorithms is provided from an overview of machine learning (ML) theory that includes history, background primer, and examples. Radar data issues of collection, application, and examples for SAR/HRR data and communication signals analysis are discussed. In addition, this book presents practical considerations of deploying such techniques, including performance evaluation, energy-efficient computing, and the future unresolved issues.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
A new algorithm is presented for Automatic Target Recognition (ATR) using High Range Resolution (HRR) profiles as opposed to traditional Synthetic Aperture Radar (SAR) images. ATR performance using SAR images degrades considerably in case of moving targets due to blurring caused in the cross-range domain. ATR based on HRR profiles, which are formed without Fourier transform in the cross-range, is expected to have superior performance for moving targets with the proposed method. One of the major contributions of this project so far has been the utilization of Eigen-templates as ATR features that are obtained via Singular Value Decomposition (SVD) of HRR profiles. SVD analysis of a large class of HRR data revealed that the Range-space eigenvectors corresponding to the largest singular value accounted for more than 90% of target energy. Hence, it has been proposed that the Range-space Eigen-vectors be used as templates for classification. The effectiveness of data normalization and Gaussianization of profile data in improving classification performance is also studied. With extensive simulation studies it is shown that the proposed Eigen-template based ATR approach provides consistent superior performance with recognition rate reaching 99.5% for the four class XPATCH database. This research project is being conducted in direct collaboration with the Sensors Directorate's ATR Assessment Branch, Wright Laboratories, Wright-Patt AFB, Dayton, Ohio, where it is being monitored by Dr. Rob Williams. A primary objective df this collaborative effort is to complement and augment various other ongoing research activities being conducted or supported by the Wright Labs ATR research team.
Author: P. Tait
Publisher: IET
ISBN: 0863415016
Category : Technology & Engineering
Languages : en
Pages : 428
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Book Description
This book text provides an overview of the radar target recognition process and covers the key techniques being developed for operational systems. It is based on the fundamental scientific principles of high resolution radar, and explains how the underlying techniques can be used in real systems, taking into account the characteristics of practical radar system designs and component limitations. It also addresses operational aspects, such as how high resolution modes would fit in with other functions such as detection and tracking.
Author: Vijay Bhatnagar
Publisher:
ISBN:
Category : Image processing
Languages : en
Pages : 94
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Book Description
Author: Rajesh Vashist
Publisher:
ISBN:
Category : Image processing
Languages : en
Pages : 158
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Book Description
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 130
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Book Description
Fully polarized Xpatch signatures are transformed to two left circularly polarized signals. These two signals are then filtered by a linear FM pulse compression ('chirp') transfer function, corrupted by AWGN, and filtered by a filter matched to the 'chirp' transfer function. The bandwidth of the 'chirp' radar is about 750 MHz. Range profile feature extraction is performed using the TLS Prony Model parameter estimation technique developed at Ohio State University. Using the Prony Model, each scattering center is described by a polarization ellipse, relative energy, frequency response, and range. This representation of the target is vector quantized using a K-means clustering algorithm. Sequences of vector quantized scattering centers as well as sequences of vector quantized range profiles are used to synthesize target specific Hidden Markov Models (HMM's). The identification decision is made by determining which HMM has the highest probability of generating the unknown sequence. The data consist of synthesized Xpatch signatures of two targets which have been difficult to separate with other RTI algorithms. The RTI algorithm developed for this thesis is clearly able to separate these two targets over a 10 by 10 degree (1 degree granularity) aspect angle window off the nose for SNRs as low as 0 dB. The classification rate is 100 % for SNRs of 5 - 20 dB, 95 % for a SNR of 0 dB and it drops rapidly for SNRs lower than 0 dB.
Author: Brett Borden
Publisher: CRC Press
ISBN: 9781420069006
Category : Science
Languages : en
Pages : 166
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Book Description
Radar-based imaging of aircraft targets is a topic that continues to attract a lot of attention, particularly since these imaging methods have been recognized to be the foundation of any successful all-weather non-cooperative target identification technique. Traditional books in this area look at the topic from a radar engineering point of view. Consequently, the basic issues associated with model error and image interpretation are usually not addressed in any substantive fashion. Moreover, applied mathematicians frequently find it difficult to read the radar engineering literature because it is jargon-laden and device specific, meaning that the skills most applicable to the problem's solution are rarely applied. Enabling an understanding of the subject and its current mathematical research issues, Radar Imaging of Airborne Targets: A Primer for Applied Mathematicians and Physicists presents the issues and techniques associated with radar imaging from a mathematical point of view rather than from an instrumentation perspective. The book concentrates on scattering issues, the inverse scattering problem, and the approximations that are usually made by practical algorithm developers. The author also explains the consequences of these approximations to the resultant radar image and its interpretation, and examines methods for reducing model-based error.
Author:
Publisher:
ISBN:
Category : Airplanes
Languages : en
Pages : 314
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Book Description
Contains the unclassified papers presented at the Symposium. Novel solutions to the Non-Cooperative Target Identification (NCTI) Problem, using radar are proposed. The papers are presented under the following headings: System requirements -- Target characterisation -- Radar measurements and feature extraction -- Target classification -- Scattering techniques, target modelling and validation.
