Autonomous Time-frequency Cropping and Feature-extraction Algorithms for Classification of LPI Radar Modulations PDF Download
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Author: Publisher: ISBN: Category : Algorithms Languages : en Pages : 78
Book Description
Three autonomous cropping and feature extraction algorithms are examined that can be used for classification of low probability of intercept radar modulations using time-frequency (T-F) images. The first approach, Erosion Dilation Adaptive Binarization (EDAB), uses erosion and a new adaptive threshold binarization algorithm embedded within a recursive dilation process to determine the modulation energy centroid (radar's carrier frequency) and properly place a fixed-width cropping window. The second approach, Marginal Frequency Adaptive Binarization (MFAB), uses the marginal frequency distribution and the adaptive threshold binarization algorithm to determine the start and stop frequencies of the modulation energy to locate and adapt the size of the cropping window. The third approach, Fast Image Filtering, uses the fast Fourier transform and a Gaussian lowpass filter to isolate the modulation energy. The modulation is then cropped from the original T-F image and the adaptive binarization algorithm is used again to compute a binary feature vector for input into a classification network. The binary feature vector allows the image detail to be preserved without overwhelming the classification network that follows. A multi-layer perceptron and a radial basis function network are used for classification and the results are compared. Classification results for nine simulated radar modulations are shown to demonstrate the three feature-extraction approaches and quantify the performance of the algorithms. It is shown that the best results are obtained using the Choi-Williams distribution followed by the MFAB algorithm and a multi-layer perceptron. This setup produced an overall percent correct classification (Pcc) of 87.2% for testing with noise variation and 77.8% for testing with modulation variation. In an operational context, the ability to process and classify LPI signals autonomously allows the operator in the field to receive real-time results.
Author: Publisher: ISBN: Category : Algorithms Languages : en Pages : 78
Book Description
Three autonomous cropping and feature extraction algorithms are examined that can be used for classification of low probability of intercept radar modulations using time-frequency (T-F) images. The first approach, Erosion Dilation Adaptive Binarization (EDAB), uses erosion and a new adaptive threshold binarization algorithm embedded within a recursive dilation process to determine the modulation energy centroid (radar's carrier frequency) and properly place a fixed-width cropping window. The second approach, Marginal Frequency Adaptive Binarization (MFAB), uses the marginal frequency distribution and the adaptive threshold binarization algorithm to determine the start and stop frequencies of the modulation energy to locate and adapt the size of the cropping window. The third approach, Fast Image Filtering, uses the fast Fourier transform and a Gaussian lowpass filter to isolate the modulation energy. The modulation is then cropped from the original T-F image and the adaptive binarization algorithm is used again to compute a binary feature vector for input into a classification network. The binary feature vector allows the image detail to be preserved without overwhelming the classification network that follows. A multi-layer perceptron and a radial basis function network are used for classification and the results are compared. Classification results for nine simulated radar modulations are shown to demonstrate the three feature-extraction approaches and quantify the performance of the algorithms. It is shown that the best results are obtained using the Choi-Williams distribution followed by the MFAB algorithm and a multi-layer perceptron. This setup produced an overall percent correct classification (Pcc) of 87.2% for testing with noise variation and 77.8% for testing with modulation variation. In an operational context, the ability to process and classify LPI signals autonomously allows the operator in the field to receive real-time results.
Author: Publisher: ISBN: Category : Algorithms Languages : en Pages : 195
Book Description
In this thesis, an autonomous feature extraction algorithm for classification of Low Probability of Intercept (LPI) radar modulations is investigated. A software engineering architecture that allows a full investigation of various preprocessing algorithms and classification techniques is applied to a database of important LPI radar waveform modulations including Frequency Modulation Continuous Waveform (FMCW), Phase Shift Keying (PSK), Frequency Shift Keying (FSK) and combined PSK and FSK. The architecture uses time-frequency detection techniques to identify the parameters of the modulation. These include the Wigner-Ville distribution, the Choi-Williams distribution and quadrature mirror filtering. Autonomous time-frequency image cropping algorithm is followed by a feature extraction algorithm based on principal components analysis. Classification networks include the multilayer perceptron, the radial basis function and the probabilistic neural networks. Lastly, using image processing techniques on images obtained by the Wigner-Ville distribution and the Choi-Williams distribution, two autonomous extraction algorithms are investigated to derive the significant modulation parameters of polyphase coded LPI radar waveform modulations.
Author: Phillip E. Pace Publisher: Artech House ISBN: 159693235X Category : Technology & Engineering Languages : en Pages : 893
Book Description
"This comprehensive book presents LPI radar design essentials, including ambiguity analysis of LPI waveforms, FMCW radar, and phase-shift and frequency-shift keying techniques. Moreover, you find details on new OTHR modulation schemes, noise radar, and spatial multiple-input multiple-output (MIMO) systems. The book explores autonomous non-linear classification signal processing algorithms for identifying LPI modulations. It also demonstrates four intercept receiver signal processing techniques for LPI radar detection that helps you determine which time-frequency, bi-frequency technique best suits any LPI modulation of interest."--Publisher.
Author: Pradip Kumar Jain Publisher: Springer Nature ISBN: 9811955506 Category : Technology & Engineering Languages : en Pages : 515
Book Description
This book comprises select proceedings of the International Conference on Advances in Signal Processing and Communication Engineering (ICASPACE 2021). The book covers several theoretical and mathematical approaches addressing day-to-day challenges in signal, image, and speech processing and advanced communication systems. It primarily focuses on effective mathematical methods, algorithms, and models that enhance the performance of existing systems. The topics covered in the book are advances in signal processing (radar and biomedical), image processing, speech processing, technical and environmental challenges in 5G technology, and strategies for optimal utilization of resources to improve the efficacy of the communication systems in terms of bandwidth and radiating power, etc. The works published in the book will remarkably be helpful to prospective scholars, academicians, and students seeking knowledge in signal processing and communication engineering.
Author: Amine Nait-Ali Publisher: Springer Science & Business Media ISBN: 354089506X Category : Technology & Engineering Languages : en Pages : 384
Book Description
Generally speaking, Biosignals refer to signals recorded from the human body. They can be either electrical (e. g. Electrocardiogram (ECG), Electroencephalogram (EEG), Electromyogram (EMG), etc. ) or non-electrical (e. g. breathing, movements, etc. ). The acquisition and processing of such signals play an important role in clinical routines. They are usually considered as major indicators which provide clinicians and physicians with useful information during diagnostic and monitoring processes. In some applications, the purpose is not necessarily medical. It may also be industrial. For instance, a real-time EEG system analysis can be used to control and analyze the vigilance of a car driver. In this case, the purpose of such a system basically consists of preventing crash risks. Furthermore, in certain other appli- tions,asetof biosignals (e. g. ECG,respiratorysignal,EEG,etc. ) can be used toc- trol or analyze human emotions. This is the case of the famous polygraph system, also known as the “lie detector”, the ef ciency of which remains open to debate! Thus when one is dealing with biosignals, special attention must be given to their acquisition, their analysis and their processing capabilities which constitute the nal stage preceding the clinical diagnosis. Naturally, the diagnosis is based on the information provided by the processing system.
Author: Bassem R. Mahafza Publisher: CRC Press ISBN: 1420066447 Category : Mathematics Languages : en Pages : 500
Book Description
Offering radar-related software for the analysis and design of radar waveform and signal processing, Radar Signal Analysis and Processing Using MATLAB provides a comprehensive source of theoretical and practical information on radar signals, signal analysis, and radar signal processing with companion MATLAB code. Aft
Author: Uttam K. Majumder Publisher: Artech House ISBN: 1630816396 Category : Technology & Engineering Languages : en Pages : 290
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: 9781423572381 Category : Languages : en Pages : 605
Book Description
This handbook is designed to aid electronic warfare and radar systems engineers in making general estimations regarding capabilities of systems. It is not intended as a detailed designer's guide, due to space limitations. Portions of the handbook and future changes will be posted on an internet link.
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Author: Phillip E. Pace
Author: Pradip Kumar Jain
Author: Institution of Electrical Engineers
Author: Amine Nait-Ali
Author: Bassem R. Mahafza
Author: Uttam K. Majumder
Author: 
Author: David George Croft Luck