Target recognition techniques for multifunction phased array radar. 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. Abebooks, an amazon company, offers millions of new, used, and outofprint books. It is based on the fundamental scientific principles of high resolution radar. The goal of this method is to maximize the betweenclass distance, while preserving the withinclass structure. 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. The article presents a fuzzy expert system designed to determine the possible radar range of the ars880. The book is based on the fundamental scientific principles of high resolution radar, and explains how the. The iet shop radar automatic target recognition atr. This approach achieves good classification performance by constructing a geometric structure in subprofile space.
Cognitive radar for target tracking in multipath scenarios. In this paper, the recognition combination will be presented using fuzzy fusion based on three classifiers. Nowadays, it is viewed as an authentic means to fix the issue of target recognition. Radar target recognition by fuzzy logic ieee conference publication. 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. Fuzzy logic classifier a simple implementation of a scalar discriminant based classification.
Fuzzy logic classification of sband polarimetric radar echoes to identify threebody scattering and improve data quality. We address the problem of adaptive waveform design for extended target recognition in cognitive radar networks. Tait, institution of electrical engineers staff contribution by. For student paper competition cognitive radar for target tracking in multipath scenarios phani chavali, student member, ieee and arye nehorai. 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.
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. One of the applications for the decisionmaking and automation system design is the fuzzy logic system. 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. Pdf fuzzy fusion system for radar target recognition. A novel fuzzy based approach for multiple target detection in mimo. Radar is really a effective tool for discovering and tracking airborne targets for example aircraft and missiles by night and day. An improved decision fusion technique to increase the. A fuzzy fusion system is constructed to combine multiple classifiers in. Radar target recognition thesis writing i help to study. With the increased availability of coherent wideband radars there has been a renewed interest in radar target recognition. Automatic radar target recognition system at thz frequency band. A fuzzylogic based non cooperative target recognition thomas boulay, julien lagoutte surface radar thales air systems limours, france thomas. Numerous and frequentlyupdated resource results are available from this search.
Processing directed towards the above application areas includes advances in waveform. Radar target recognition based on fuzzy optimal transformation using highresolution range profile. Radar imaging, as understood here, involves target recognition, i. Recognition matrix of an aerial target is established first. This paper deals with the problem of multiple target detection in mimo radar. A fuzzy logic algorithm for the wsr88d cathy kessinger, scott ellis, and joseph van andel national center for atmospheric research boulder, co 80305 1. Biologically inspired target recognition in radar sensor. Suppose that many sensors are deployed to localise a target using the tdoa method. Deep learning for endtoend automatic target recognition. 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. 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.
Pdf ground surveillance radar target classification. The book is about fuzzy logic control and its applications. In locating a target, nonlineofsight nlos errors exist in the case where an obstacle blocks the lineofsight path between the sensor and the target. A fuzzy logic based non cooperative target recognition thomas boulay, julien lagoutte surface radar thales air systems limours, france thomas. In this paper, a novel fuzzy optimal transformation fot method for radar target recognition using highresolution range profile hrrp is proposed.
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. Automatic target recognition for sar images based on fuzzy. A fuzzylogic based non cooperative target recognition. Joint sensor selection and power allocation algorithm for multiple. A fuzzy logic technique for identifying nonprecipitating. Maritime radar is the kernel sensor for tracking vessels in vessel traffic service system, it is important for maritime situation awareness. It has a feature of shape recognition using objects boundary signatures. It can be inferred from the recent w orks reported in. However, the images collected by the maritime radar are inundated with excessive noise blips, which bring variety of troubles in extraction of ship targets.
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. His active research interests are digital image processing, machine learning, pattern recognition, remote sensing image analysis and fuzzy logic. Abstract this thesis is concerned with methods to facilitate automatic target recognition using images generated from a group of associated radar systems. Physics equipment performance evaluation fuzzy algorithms fuzzy logic fuzzy systems integrals radar properties radar systems target acquisition equipment and supplies. A recognition approach of radar blips based on improved. Introduction to radar target recognition electromagnetics. Everything every driver, and the police, should know about traffic speed radar angle of arrival estimation using radar interferometry.
Expert users of the wsr88d data provided the truth data sets used to optimize the algorithm performances. 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. The empirical evidence of the effectiveness of this approach makes it of the main current directions in target recognition research. The fuzzy logic approach to the automatic classification of moving target detected by ground surveillance radar is presented in this paper.
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. Introduction to radar target recognition ebook, 2005. This book provides an overview of the whole radar target recognition process, and covers the key techniques being developed for operational systems. Target classification based on a combination of possibility and. Here youll find current best sellers in books, new releases in books, deals in books, kindle ebooks, audible audiobooks, and so much more. A statistical theory of target detection by pulsed radar. The hardcover of the introduction to radar target recognition by p. Fuzzy logic and fuzzy set theory based edge detection algorithm.
Air targets recognition using a fuzzy logic approach. In this paper, we propose a novel radar hrrp target recognition method, namely fuzzy optimal transformation fot. The real audio doppler signatures of various targets are. Fuzzy logic classifier design for air targets recognition. For a practical, technician level, approach you could do a lot worse than the us navy electronics technician training guides. A second fuzzy logic algorithm then uses the cluttersuppressed radar snr measurements to determine the depth of the mixing layer. Advanced approaches are required for this, and several of recent interest are discussed in this book. 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. An improved decision fusion technique to increase the performance level of hrr atr systems. Introduction the radar echo classifier rec is a data fusion system that uses fuzzylogic techniques kosko, 1992 to. Mar 03, 2020 time difference of arrival tdoa method is widely utilised to locate a target emitting a signal. 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.
Ground surveillance radar target classification based on. Target tracking using fuzzy logic with shape recognition. Dec 21, 2009 we apply fuzzy logic system fls to automatic target detection based on the ac power values from dct. Here youll find current best sellers in books, new releases in books, deals in books, kindle. As in commercial electronics and communications, the evolution from purely analog designs to hybrid analogdigital designs continues to drive advances. Using fuzzy logic expert system for the estimation of the. Fuzzy logic classification of sband polarimetric radar echoes to identify threebody scattering and improve data quality authors. In this paper, we propose a novel radar hrrp target recognition. Complete processing system that uses fuzzy logic for ship detection in sar images.
This example shows how to model and simulate the output of an automotive radar sensor for different driving scenarios. Fuzzy fusion system for radar target recognition imen jdey, abdelmalek toumi, ali. The problem with a fuzzy system is it is difficult to deal w ith too many features, membership functions, andor rules. This book provides an overview of the whole radar target recognition process, and covers the key. The application of intuitionistic fuzzy theory in radar. Pdf automatic radar target recognition system at thz. Reliable information about the coronavirus covid19 is available from the world health organization current situation, international travel. 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. The books homepage helps you explore earths biggest bookstore without ever leaving the comfort of your couch. Handbook of theory and practice covers a set of graphical solutions to the detection problem, designated as meyer plots, for radar systems design. A statistical theory of target detection by pulsed radar author. Target recognition using the timefrequency representation of the impulse.
Fuzzy logic is one approach to meeting this challenge and providing reliability and power 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 mer. Current status and future possibilities volume 50 issue 2 vincent y. Oclcs webjunction has pulled together information and resources to assist library staff as they consider how to handle. A new algorithm for phased array radar search function. Radar target classification technologies intechopen. These approaches use probabilistic and estimation techniques, kalman filters, fuzzy logic, neural networks 3. 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. 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 new text provides an overview of the whole radar target recognition process, and covers the key techniques being developed for operational systems. A study to obtain the probability that a pulsedtype radar system will. Artificial intelligence and radar target tracking gerard t. 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.
However, the images collected by the maritime radar are inundated with excessive noise blips, which bring variety of. Fuzzy set theory has been extensively used in clustering problems where the task is to provide class. Ioap sciforum preprints scilit sciprofiles mdpi books encyclopedia mdpi blog. Drawbacks of some previously proposed methods are analyzed, and then a novel algorithm is presented. The iet shop introduction to radar target recognition. For tactical radars it is important to consider target tracking. This book text provides an overview of the radar target recognition process and covers the key techniques being developed for operational systems.
The statistical results show that the proposed algorithm f. Abstract target recognition and tracking is a very important research area in pattern recognition. Neurofuzzy logic for partsbased reasoning about complex scenes in remotely sensed data paper 1142316. Signal processing, sensorinformation fusion, and target. The book is based on the fundamental scientific principles of high resolution radar, and explains how the techniques can be used in real. 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. Introduction to radar target recognition electromagnetics and radar p. On last generation radars, pattern recognition is used to classify known echos in different categories. Neural networks, are highly suited for large amounts of features and classes. Fuzzy models and algorithms for pattern recognition and image. Introduction to radar target recognition book, 2005.
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. Author links open overlay panel daiying zhou xiaofeng shen wanlin yang. Pdf a fuzzylogic non cooperative target recognition. Modern radar processors make possible the realtime identification and filtering of ap clutter.
Algorithm for target recognition based on intervalvalued. A radar systems major purpose is the detection and location of an object by means of a return signal, which could be either a reflection or a beacon. 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. Mar 02, 2010 this is our project design entitled target tracking and shooting using fuzzy logic. Unique to this volume in the kluwer handbooks of fuzzy sets series is the. Zadeh introduced the term fuzzy logic in his seminal work fuzzy sets, which. Radar target recognition by fuzzy logic ieee journals. Print, cd, and pdf versions are available from this company.
A recognition approach of radar blips based on improved fuzzy. 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. Fuzzy sets in pattern recognition and machine intelligence. Target recognition and tracking based on data fusion of. The aim of the project is to develop a fuzzy controller which will allow generat. 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. 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. Fuzzy logic based spatial bird detection with weather radar. A fuzzy pattern recognition method of radar signal based. 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.
Fuzzy logic classification of sband polarimetric radar. Extended target recognition in cognitive radar networks. The calculation by using the fuzzy logic module works slightly different. In 4, 5 two methods based on fuzzy and hard logic were considered for adaptively. In this paper, a fuzzy logic approach type1 fuzzy logic classifier t1flc is proposed to improve flight recognition ratio.
Resonance processing of fmcw radar returns for accurate perimeterbreach detection of a flattrajectory quasicylindrical target conference presentation. Pal fuzzy sets and systems 156 2005 3886 383 suggested by zadeh. 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. 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. As a result of analysis, input and output variables with corresponding membership function are defined. Generating synthetic radar detections is important for testing and validating tracking and sensor fusion algorithms in corner. 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. Subsequently, multivalued recognition system and fuzzy knn rule, among others, have been developed in the supervised framework. A fuzzy logic enhanced kalman filter was developed to fuse the information from machine vision, laser radar, imu, and speed sensor. Introduction to radar target recognition researchgate. Colinradar target recognition by fuzzy logic, ieee aerospace and electronic systems magazine.
Knowledge based radar detection, tracking, and classi. Aim at multipletarget tracking mtt, a joint radar node selection and power. Although the existing algorithms are shown to be effective. The fuzzy logic classifier is made up of four parts. The sensor system for path finding consists of machine vision and laser radar. Automatic target recognition systems mostly employ fusion strategies for this aim. The real audio doppler signatures of various targets are analyzed by spectrogram.
325 1117 298 1497 981 1457 1477 1192 813 1272 1617 1595 1432 1095 704 1303 303 596 1075 81 1436 94 1329 1317 293 82 812 416 577 1190 1274 937 779 802 822