Download or read book Robust High Range Resolution Radar Target Identification Using a Statistical Feature Based Classifier with Feature Level Fusion written by Richard Alan Mitchell and published by . This book was released on 1997 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Non cooperative Air Target Identification Using Radar written by and published by . This book was released on 1998 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Algorithms for Synthetic Aperture Radar Imagery written by and published by . This book was released on 2000 with total page 748 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Sensor Fusion Architectures Algorithms and Applications written by and published by . This book was released on 1999 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Target Recognition Using Linear Classification of High Range Resolution Radar Profiles written by Ricardo A. Diaz and published by . This book was released on 2004-03-01 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Robust High Range Resolution Radar for Target Classification written by Michel P. Zumwalt (MAJ, USAF.) and published by . This book was released on 2000 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advances and Applications of DSmT for Information Fusion Collected Works Volume 4 written by Florentin Smarandache and published by Infinite Study. This book was released on 2015-07-01 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fourth volume on Advances and Applications of Dezert-Smarandache Theory (DSmT) for information fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics. The contributions have been published or presented after disseminating the third volume (2009, http://fs.gallup.unm.edu/DSmT-book3.pdf) in international conferences, seminars, workshops and journals.
Download or read book Advances and Applications of DSmT for Information Fusion Vol IV written by Florentin Smarandache, Jean Dezert and published by Infinite Study. This book was released on 2015-03-01 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fourth volume on Advances and Applications of Dezert-Smarandache Theory (DSmT) for information fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics. The contributions (see List of Articles published in this book, at the end of the volume) have been published or presented after disseminating the third volume (2009, http://fs.gallup.unm.edu/DSmT-book3.pdf) ininternational conferences, seminars, workshops and journals.
Download or read book International Aerospace Abstracts written by and published by . This book was released on 1999 with total page 1016 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Classification of Ultra High Range Resolution Radar Using Decision Boundary Analysis written by and published by . This book was released on 1994 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis examines the discrimination of targets with Ultra High Range Resolution (UHRR) radar data. Using these measured signals from frontal aspect angles of four aircraft classes, the baseline performance of the Adaptive Gaussian Classifier (AGC) is tested with respect to aligning exemplars to templates. Alignment plays a crucial role in the AGC's classification performance which can degrade by 11% for a target class. The AGC is compared to non-parametric classifiers, but no statistically significant degradation of performance is found. Data separability is analyzed by hounding the Bayes error. The data is well separated in a statistical sense. A feature selection algorithm based on analysis of the decision boundary, is applied to find a reduced feature set, which are linear combinations of the original features. These features are optimized with respect to classification error rather than reconstruction error. This technique is extended to deduce the relevant features in the original feature space. Fewer than 5% of the features in the original feature space may be used to attain an improved classification rate. This new method is a true reduction of features and shows improvement up to 15%. Discrimination of UHRR radar signatures using a multiresolution analysis is proposed. The decision boundary analysis chooses relevant wavelet scales with respect to classification. Some improved performance against an entropy based measure is observed for limited feature sets. The technique developed here successfully chooses the scale that causes classification performance to peak within 5% of the performance in the full-dimensional or reduced-dimensional UHRR radar signature space.
Download or read book Dissertation Abstracts International written by and published by . This book was released on 2008 with total page 1006 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book High Range Resolution Radar Target Identification Using the Prony Model and Hidden Markov Models written by and published by . This book was released on 1992 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Millimeter Wave Radar written by Stephen L. Johnston and published by . This book was released on 1980 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Pattern Recognition for Synthetic Aperture Radar SAR Automatic Target Recognition ATR written by and published by . This book was released on 2001 with total page 79 pages. Available in PDF, EPUB and Kindle. Book excerpt: State-of-the-art research on spectral estimation, feature extraction, and pattern recognition algorithms are presented for radar signal processing and automatic target recognition. Advanced space-time spectral estimation algorithms are presented for multiple moving target feature extraction as well as clutter and jamming suppression for airborne high range resolution (HRR) phased-array radar. A nonparametric adaptive filtering-based approach, referred to as the Gapped-data Amplitude and Phase EStimation (GAPES) algorithm, is proposed for the spectral analysis of gapped data sequences as well as synthetic aperture radar (SAR) imaging with angle diversity data fusion. A QUasi-parametric ALgorithm for target feature Extraction (QUALE) algorithm is also investigated for angle diversity data fusion. Support Vector Machines (SVMs) as compared with other advanced classifiers in the MSTAR Public Domain Release and HRR data are found to outperform neural networks and matched filters. A new concept to create negative examples from the known target class is presented and shown to tremendously improve the rejection of confusers. Finally, Information Theoretic Learning (ITL) is proposed as a new algorithm to demix HRR signatures of closely parked targets.
Download or read book American Doctoral Dissertations written by and published by . This book was released on 1997 with total page 806 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Deep Learning for Radar and Communications Automatic Target Recognition written by Uttam K. Majumder and published by Artech House. This book was released on 2020-07-31 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book High Range Resolution Radar Target Identification Using the Prony Model and Hidden Markov Models written by Mark R. DeWitt (CAPT, USAF.) and published by . This book was released on 1992 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
