Abstract target recognition and tracking is a very important research area in pattern recognition. Radar automatic target recognition atr and noncooperative target recognition nctr explores both the fundamentals of classification techniques applied to data from a variety of radar modes and selected advanced techniques at the forefront of research, and is essential reading for academic, industrial and military radar researchers, students. While there are a fairly large number of radar books available, this is the first that i have read that lays out the signal processing aspects of radar. Artificial intelligence and radar target tracking gerard t. Suppose that many sensors are deployed to localise a target using the tdoa method. This book provides an overview of the whole radar target recognition process, and covers the key. In this paper, the recognition combination will be presented using fuzzy fusion based on three classifiers. This book text provides an overview of the radar target recognition process and covers the key techniques being developed for operational systems.
Handbook of theory and practice covers a set of graphical solutions to the detection problem, designated as meyer plots, for radar systems design. The book is about fuzzy logic control and its applications. Aim at multipletarget tracking mtt, a joint radar node selection and power. Target tracking using fuzzy logic with shape recognition. A fuzzy fusion system is constructed to combine multiple classifiers in. Oclcs webjunction has pulled together information and resources to assist library staff as they consider how to handle. Fuzzy inference systems a fuzzy inference system fis is a system that uses fuzzy set theory to map inputs features in the case of fuzzy cla. Radar target classification technologies intechopen. Introduction the radar echo classifier rec is a data fusion system that uses fuzzylogic techniques kosko, 1992 to. Ioap sciforum preprints scilit sciprofiles mdpi books encyclopedia mdpi blog.
Author links open overlay panel daiying zhou xiaofeng shen wanlin yang. The application of intuitionistic fuzzy theory in radar. Zadeh introduced the term fuzzy logic in his seminal work fuzzy sets, which. The iet shop introduction to radar target recognition. It can be inferred from the recent w orks reported in. Here youll find current best sellers in books, new releases in books, deals in books, kindle. 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. Pdf automatic radar target recognition system at thz. Fuzzy set theory has been extensively used in clustering problems where the task is to provide class. The goal of this method is to maximize the betweenclass distance, while preserving the withinclass structure. Recognition matrix of an aerial target is established first.
This new text provides an overview of the whole radar target recognition process, and covers the key techniques being developed for operational systems. Automatic target recognition for sar images based on fuzzy. Pal fuzzy sets and systems 156 2005 3886 383 suggested by zadeh. The book is based on the fundamental scientific principles of high resolution radar, and explains how the techniques can be used in real. The book is based on the fundamental scientific principles of high resolution radar, and explains how the.
A study to obtain the probability that a pulsedtype radar system will. Radar target recognition based on fuzzy optimal transformation using highresolution range profile. Extended target recognition in cognitive radar networks. By the fundamental notion in atanassovs intuitionistic fuzzy sets ifs, synthetically considering the effects of both the membership and the nonmember ship degrees, seven calculating methods of similarity degree for intuitionistic fuzzy, i. He is currently a phd student in the information and communication technologies at the department of information engineering and computer science at the university of trento, italy. Abebooks, an amazon company, offers millions of new, used, and outofprint books. A recognition approach of radar blips based on improved. Using fuzzy logic expert system for the estimation of the. Numerous and frequentlyupdated resource results are available from this search. Current status and future possibilities volume 50 issue 2 vincent y. A fuzzy logic based non cooperative target recognition thomas boulay, julien lagoutte surface radar thales air systems limours, france thomas. The problem with a fuzzy system is it is difficult to deal w ith too many features, membership functions, andor rules. Mar 03, 2020 time difference of arrival tdoa method is widely utilised to locate a target emitting a signal.
Introduction to radar target recognition book, 2005. A fuzzy pattern recognition method of radar signal based. Introduction to radar target recognition electromagnetics and radar p. Fuzzy fusion system for radar target recognition imen jdey, abdelmalek toumi, ali. Fuzzy logic and fuzzy set theory based edge detection algorithm. Nowadays, it is viewed as an authentic means to fix the issue of target recognition. Pdf a fuzzylogic non cooperative target recognition. A second fuzzy logic algorithm then uses the cluttersuppressed radar snr measurements to determine the depth of the mixing layer. Algorithm for target recognition based on intervalvalued. This technique first applies a fuzzy logic algorithm to the radar spectra to reduce the influence of clutter from a variety of sources, including ground clutter, radio frequency interference, and point targets. Pdf fuzzy fusion system for radar target recognition. Dec 21, 2009 we apply fuzzy logic system fls to automatic target detection based on the ac power values from dct.
The calculation by using the fuzzy logic module works slightly different. A new algorithm for phased array radar search function. Motivated by the unique character of fuzzy logic system, simultaneously handling numerical data and linguistic knowledge, and the promising knowledgebased approach, we propose an flsbased approach to sar atr. After a presentation of the parameters which can be delivered by signal and data processing, the paper gives a description of an algorithm including both spatial and temporal mer. In this paper, we propose a novel radar hrrp target recognition. Drawbacks of some previously proposed methods are analyzed, and then a novel algorithm is presented.
Annotation the three volume set lncs 449144924493 constitutes the refereed proceedings of the 4th international symposium on neural networks, isnn 2007, held in nanjing, china in june 2007. This approach achieves good classification performance by constructing a geometric structure in subprofile space. These approaches use probabilistic and estimation techniques, kalman filters, fuzzy logic, neural networks 3. Colinradar target recognition by fuzzy logic, ieee aerospace and electronic systems magazine. Automatic target recognition atr generally refers to the autonomous or aided target detection and recognition by computer processing of data from a variety of sensors such as forward looking infrared flir, synthetic aperture radar sar, inverse synthetic aperture radar isar, laser radar ladar, millimeter wave mmw radar, multispectral. Tait, institution of electrical engineers staff contribution by.
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. A fuzzy logic enhanced kalman filter was developed to fuse the information from machine vision, laser radar, imu, and speed sensor. However, the images collected by the maritime radar are inundated with excessive noise blips, which bring variety of. Resonance processing of fmcw radar returns for accurate perimeterbreach detection of a flattrajectory quasicylindrical target conference presentation. Fuzzy logic based spatial bird detection with weather radar. Fuzzy logic classifier design for air targets recognition. May 24, 2007 annotation the three volume set lncs 449144924493 constitutes the refereed proceedings of the 4th international symposium on neural networks, isnn 2007, held in nanjing, china in june 2007. This example shows how to model and simulate the output of an automotive radar sensor for different driving scenarios. Fuzzy sets in pattern recognition and machine intelligence.
Introduction to radar target recognition researchgate. As in commercial electronics and communications, the evolution from purely analog designs to hybrid analogdigital designs continues to drive advances. Reliable information about the coronavirus covid19 is available from the world health organization current situation, international travel. Fuzzy logic and fuzzy set theory based edge detection algorithm 111 another way to detect edges in a digital image is to use fuzzy logic fl. Considering this point, a fuzzy pattern recognition method based on neural network getting weights to radar signal recognition is studied in this paper, the feature parameter weights in this method are fixed on by neural network and then the unknown radar signal is recognized by fuzzy pattern recognition method. An inertial measurement unit imu is used for detecting the tilt of the vehicle, and a speed sensor is used to find the travel speed. A fuzzy logic technique for identifying nonprecipitating. Introduction to radar target recognition electromagnetics. Fuzzy models and algorithms for pattern recognition and image. The real audio doppler signatures of various targets are.
Unique to this volume in the kluwer handbooks of fuzzy sets series is the. One of the applications for the decisionmaking and automation system design is the fuzzy logic system. Fuzzy logic is one approach to meeting this challenge and providing reliability and power quality. In this paper, we propose a novel radar hrrp target recognition method, namely fuzzy optimal transformation fot. The statistical results show that the proposed algorithm f. Target classification based on a combination of possibility and. Neurofuzzy logic for partsbased reasoning about complex scenes in remotely sensed data paper 1142316. Ground surveillance radar target classification based on. The objective of this paper is to present a method of target recognition based on the fuzzy logic principles applied to conventional and multifunction rada. However, the images collected by the maritime radar are inundated with excessive noise blips, which bring variety of troubles in extraction of ship targets. For student paper competition cognitive radar for target tracking in multipath scenarios phani chavali, student member, ieee and arye nehorai. An improved decision fusion technique to increase the performance level of hrr atr systems. A closedloop active target recognition radar system is extended to the case of a centralized cognitive radar network, in which a generalized likelihood ratio glr based sequential hypothesis testing sht framework is employed.
In this paper, a fuzzy logic approach type1 fuzzy logic classifier t1flc is proposed to improve flight recognition ratio. His active research interests are digital image processing, machine learning, pattern recognition, remote sensing image analysis and fuzzy logic. A statistical theory of target detection by pulsed radar. Fuzzy logic classification of sband polarimetric radar. Print, cd, and pdf versions are available from this company. Radar imaging, as understood here, involves target recognition, i. A fuzzylogic based non cooperative target recognition thomas boulay, julien lagoutte surface radar thales air systems limours, france thomas. Air targets recognition using a fuzzy logic approach.
In 4, 5 two methods based on fuzzy and hard logic were considered for adaptively. Neural networks, are highly suited for large amounts of features and classes. Advanced approaches are required for this, and several of recent interest are discussed in this book. A recognition approach of radar blips based on improved fuzzy. Expert users of the wsr88d data provided the truth data sets used to optimize the algorithm performances. The fuzzy logic approach to the automatic classification of moving target detected by ground surveillance radar is presented in this paper. In this paper, a novel fuzzy optimal transformation fot method for radar target recognition using highresolution range profile hrrp is proposed. A fuzzy logic algorithm for the wsr88d cathy kessinger, scott ellis, and joseph van andel national center for atmospheric research boulder, co 80305 1. Target recognition and tracking based on data fusion of. Fuzzy models and algorithms for pattern recognition and image processing presents a comprehensive introduction of the use of fuzzy models in pattern recognition and selected topics in image processing and computer vision. Radar target recognition by fuzzy logic ieee conference publication. This book provides an overview of the whole radar target recognition process, and covers the key techniques being developed for operational systems.
Knowledge based radar detection, tracking, and classi. For the spol data sets, the polarimetric variables are input into a fuzzy logic polarimetric identification pid algorithm to determine the type of radar echo return that is present. Maritime radar is the kernel sensor for tracking vessels in vessel traffic service system, it is important for maritime situation awareness. Mar 02, 2010 this is our project design entitled target tracking and shooting using fuzzy logic. On last generation radars, pattern recognition is used to classify known echos in different categories. The iet shop radar automatic target recognition atr. Here youll find current best sellers in books, new releases in books, deals in books, kindle ebooks, audible audiobooks, and so much more. Fuzzy logic classifier a simple implementation of a scalar discriminant based classification. Radar systems page 2 introducing periodic pulses constrains the radar system as well, since if a target is located beyond a range r u ct r 2 then the received pulse arrives after the next pulse has already been transmitted, resulting an.
The real audio doppler signatures of various targets are analyzed by spectrogram. Biologically inspired target recognition in radar sensor. Radar target recognition thesis writing i help to study. Fuzzy logic classification of sband polarimetric radar echoes to identify threebody scattering and improve data quality authors. Radar is really a effective tool for discovering and tracking airborne targets for example aircraft and missiles by night and day. The empirical evidence of the effectiveness of this approach makes it of the main current directions in target recognition research. Joint sensor selection and power allocation algorithm for multiple. Radar target recognition by fuzzy logic ieee journals. With the increased availability of coherent wideband radars there has been a renewed interest in radar target recognition.
Introduction to radar target recognition ebook, 2005. Simulation results show that our mledctfls and softmaxdctfls approaches perform very well in the radar sensor network target detection, whereas the existing 2d construction algorithm does not work in this study. Modern radar processors make possible the realtime identification and filtering of ap clutter. The hardcover of the introduction to radar target recognition by p. Here, based on the idea of type1 fuzzy logic system, we design our fuzzy logic classifier and employ it for calculating the ratio of recognition for each type of air target.
Target recognition using the timefrequency representation of the impulse. Pdf ground surveillance radar target classification. Deep learning for endtoend automatic target recognition. For tactical radars it is important to consider target tracking. A fuzzy logic algorithm is used to distinguish between clutter echoes and precipitation echoes and, subsequently, a clutter filter is applied to those radar resolution volumes where clutter is present. Automatic target recognition atr is the ability for an algorithm or device to recognize targets or other objects based on data obtained from sensors target recognition was initially done by using an audible representation of the received signal, where a trained operator who would decipher that sound to classify the target illuminated by the radar. It is based on the fundamental scientific principles of high resolution radar. The books homepage helps you explore earths biggest bookstore without ever leaving the comfort of your couch. A statistical theory of target detection by pulsed radar author. The article presents a fuzzy expert system designed to determine the possible radar range of the ars880.
Automatic radar target recognition system at thz frequency band. Processing directed towards the above application areas includes advances in waveform. Abstract this thesis is concerned with methods to facilitate automatic target recognition using images generated from a group of associated radar systems. Everything every driver, and the police, should know about traffic speed radar angle of arrival estimation using radar interferometry.
The aim of the project is to develop a fuzzy controller which will allow generat. The objective of this paper is to present a method of target recognition based on the fuzzy logic principles applied to conventional and multifunction radars. A fuzzylogic based non cooperative target recognition. In order to improve exact recognition ratios for aerial targets, this paper presents a novel algorithm for target recognition based on intervalvalued intuitionistic fuzzy sets with grey correlation. An improved decision fusion technique to increase the. Complete processing system that uses fuzzy logic for ship detection in sar images. Physics equipment performance evaluation fuzzy algorithms fuzzy logic fuzzy systems integrals radar properties radar systems target acquisition equipment and supplies. For a practical, technician level, approach you could do a lot worse than the us navy electronics technician training guides.
Although the existing algorithms are shown to be effective. Target recognition techniques for multifunction phased array radar. A novel fuzzy based approach for multiple target detection in mimo. It has a feature of shape recognition using objects boundary signatures. Cognitive radar for target tracking in multipath scenarios. This paper deals with the problem of multiple target detection in mimo radar. In locating a target, nonlineofsight nlos errors exist in the case where an obstacle blocks the lineofsight path between the sensor and the target. As a result of analysis, input and output variables with corresponding membership function are defined.
The sensor system for path finding consists of machine vision and laser radar. Hwa jung research and training team for future creative astrophysicists and cosmologists, department of astronomy and atmospheric sciences and center for atmospheric remote sensing, kyungpook national university, daegu, south korea. We address the problem of adaptive waveform design for extended target recognition in cognitive radar networks. Fuzzy logic classification of sband polarimetric radar echoes to identify threebody scattering and improve data quality. After a presentation of the parameters which can be delivered by signal and data processing, the paper gives a description of an algorithm including both spatial and temporal merging. The fuzzy logic classifier is made up of four parts. Signal processing, sensorinformation fusion, and target. Automatic target recognition systems mostly employ fusion strategies for this aim.
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