Download or read book Target Detection Tracking and Localization Using Multi spectral Image Fusion and RF Doppler Differentials written by and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract : It is critical for defense and security applications to have a high probability of detection and low false alarm rate while operating over a wide variety of conditions. Sensor fusion, which is the the process of combining data from two or more sensors, has been utilized to improve the performance of a system by exploiting the strengths of each sensor. This dissertation presents algorithms to fuse multi-sensor data that improves system performance by increasing detection rates, lowering false alarms, and improving track performance. Furthermore, this dissertation presents a framework for comparing algorithm error for image registration which is a critical pre-processing step for multi-spectral image fusion. First, I present an algorithm to improve detection and tracking performance for moving targets in a cluttered urban environment by fusing foreground maps from multi-spectral imagery. Most research in image fusion consider visible and long-wave infrared bands; I examine these bands along with near infrared and mid-wave infrared. To localize and track a particular target of interest, I present an algorithm to fuse output from the multi-spectral image tracker with a constellation of RF sensors measuring a specific cellular emanation. The fusion algorithm matches the Doppler differential from the RF sensors with the theoretical Doppler Differential of the video tracker output by selecting the sensor pair that minimizes the absolute difference or root-mean-square difference. Finally, a framework to quantify shift-estimation error for both area- and feature-based algorithms is presented. By exploiting synthetically generated visible and long-wave infrared imagery, error metrics are computed and compared for a number of area- and feature-based shift estimation algorithms. A number of key results are presented in this dissertation. The multi-spectral image tracker improves the location accuracy of the algorithm while improving the detection rate and lowering false alarms for most spectral bands. All 12 moving targets were tracked through the video sequence with only one lost track that was later recovered. Targets from the multi-spectral tracking algorithm were correctly associated with their corresponding cellular emanation for all targets at lower measurement uncertainty using the root-mean-square difference while also having a high confidence ratio for selecting the true target from background targets. For the area-based algorithms and the synthetic air-field image pair, the DFT and ECC algorithms produces sub-pixel shift-estimation error in regions such as shadows and high contrast painted line regions. The edge orientation feature descriptors increase the number of sub-field estimates while improving the shift-estimation error compared to the Lowe descriptor.
Download or read book Group target Tracking written by Wen-dong Geng and published by Springer. This book was released on 2016-10-01 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes grouping detection and initiation; group initiation algorithm based on geometry center; data association and track continuity; as well as separate-detection and situation cognition for group-target. It specifies the tracking of the target in different quantities and densities. At the same time, it integrates cognition into the application. Group-target Tracking is designed as a book for advanced-level students and researchers in the area of radar systems, information fusion of multi-sensors and electronic countermeasures. It is also a valuable reference resource for professionals working in this field.
Download or read book Non Cooperative Target Tracking Fusion and Control written by Zhongliang Jing and published by Springer. This book was released on 2018-06-25 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a concise and comprehensive overview of non-cooperative target tracking, fusion and control. Focusing on algorithms rather than theories for non-cooperative targets including air and space-borne targets, this work explores a number of advanced techniques, including Gaussian mixture cardinalized probability hypothesis density (CPHD) filter, optimization on manifold, construction of filter banks and tight frames, structured sparse representation, and others. Containing a variety of illustrative and computational examples, Non-cooperative Target Tracking, Fusion and Control will be useful for students as well as engineers with an interest in information fusion, aerospace applications, radar data processing and remote sensing.
Download or read book Innovative Target Tracking Techniques for Modern Radar and Sonar Systems written by Alfonso Farina and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this Special Issue is to gather recent advances and development in target tracking techniques to determine how they can be adapted for modern radar and sonar systems. After peer review, 17 articles in related areas have been accepted for publishing in this Special Issue. The published articles cover a range of topics and applications central to target tracking. There are eight papers about general multi-target tracking, including the topics of joint tracking and classification [3], adaptive estimation using clutter measurement probability [6], joint localization and tracking [7], extended target tracking [8], tracking with smoothing [11], DOA tracking [12], tracking under low detection probability [14], and sonar tracking and interception [17]. Three papers address multi-sensor multi-target tracking methods. Specifically, a multi-target estimating method for pulsed radar systems is proposed in [2], a joint dwell time and bandwidth optimization method in a radar network is proposed in [4], a and multiple marine ship tracking method with unknown backgrounds is presented in [9]. There are 2 papers [10,15] on the problem of target assignment in multi-sensor multi-target tracking. Moreover, Mallick et al. considered measures of nonlinearity of a polynomial curve in two dimensions [1], Zhao et al. explored the use of calibration targets for which the positions are known to the MPR system, to counter the loss in target localization accuracy arising from transmitter/receiver position errors [13], and Li et al. proposed an algorithm to apply the frequency diversity technique to passive azimuth estimation in [16].
Download or read book Single Pixel Target Detection Using Multispectral Background Changes written by Alfredo Lugo and published by . This book was released on 2010 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Possible methods to help a remote sensing analyst to find a static or moving single pixel target over vast areas of terrain were examined in this work. Specifically, the research deals with the particular problem of how to find these targets using multiple images of the same area that were collected with the same multispectral (6 bands) imaging sensor but with a background that changes between images. For this, hyperspectral quadratic covariance-based anomalous change detection algorithms were investigated to see if they could be used with multispectral data to find a moving target. In addition, a new method based on change vector analysis was developed to find a static target. In the case of the moving target problem, the performance of the Chronochrome, Covariance Equalization, and the Hyperbolic anomalous change detection algorithms were compared relative to each other and to a straight target detection algorithm. In addition, modifications to the covariance-based algorithms were developed that improved the results. For the static target case, various multispectral images were 'layer stacked' together. Then, the Spectral Matched Filter hyperspectral target detection algorithm was applied on these data cubes to explore if this method could help separate a real target from false alarms obtained when simply running a target detection algorithm on a multispectral data cube. The analysis demonstrated that a significant reduction in the number of false alarms can be obtained with these methods when compared to traditional Spectral Matched Filter (SMF) algorithm to find either static or dynamic single pixel targets of interest. In addition, the analysis shows the limitations and behavior of these methods under some of the issues normally encountered in remote sensing imaging. Overall, it was demonstrated that periodic multispectral imagery collections over a wide area can be very useful to find targets of interest."--Abstract.
Download or read book Image Processing for Remote Sensing written by C.H. Chen and published by CRC Press. This book was released on 2007-10-17 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Edited by leaders in the field, with contributions by a panel of experts, Image Processing for Remote Sensing explores new and unconventional mathematics methods. The coverage includes the physics and mathematical algorithms of SAR images, a comprehensive treatment of MRF-based remote sensing image classification, statistical approaches for improved classification with the remote sensing data, Wiener filter-based method, and other modern approaches and methods of image processing for remotely sensed data. Each chapter explores a technique for dealing with a specific remote sensing problem. The book offers physical insights on the steps for constructing various digital seismic images. The volume examines image modeling, statistical image classifiers, change detection, independent component analysis, vertex component analysis, image fusion for better classification. It explores unique topics such as accuracy assessment and information-theoretic measure of multiband images and many chapters emphasize issues with synthetic aperture radar (SAR) images. Continued development on imaging sensors creates new opportunities and challenges in image processing for remote sensing. Image Processing for Remote Sensing not only presents the most up to date developments of image processing for remote sensing but also suggests to readers the many challenging problems ahead for further study.
Download or read book Target Detection in Hyperspectral and Multispectral Images Using Projection Pursuit written by Nilofar Azizi and published by . This book was released on 2007 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multiresolution Multi Scale Target Identification and Tracking Using the Anisotropic Diffusion Pyramid written by Scott Acton and published by . This book was released on 1998 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt: A three year ARO Young Investigator project has resulted in a novel target identification and tracking system based on multiresolution, multi-scale image processing methods. Through this research effort, two nonlinear image processing methods have been developed and utilized in target tracking: the anisotropic diffusion pyramid and the morphological pyramid. Coarse-to-fine target searches are implemented within the image pyramids, providing a lOOX improvement in computational expense over standard correlation-based approaches. Several improvements in tracking robustness have been achieved, including a lOX improvement in target localization over standard linear processing methods. A noise-resilient morphological diffusion method has been designed, and diffusion techniques that converge rapidly to locally monotonic signals have been developed, yielding a significant advance in nonlinear diffusion-based image processing. Further improvements to the diffusion technique have included the incorporation of multigrid methods and the generalization to multispectral imagery for multisensor tracking applications. These advances in theory have been validated with a new tracking simulator, in which several visible-wavelength and infrared image sequences have been used for testing. During the last three years, the ARO-funded project has supported 10 graduate students at Oklahoma State University and has led to over 20 refereed publications.
Download or read book Random Finite Sets for Robot Mapping SLAM written by John Stephen Mullane and published by Springer Science & Business Media. This book was released on 2011-05-19 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: The monograph written by John Mullane, Ba-Ngu Vo, Martin Adams and Ba-Tuong Vo is devoted to the field of autonomous robot systems, which have been receiving a great deal of attention by the research community in the latest few years. The contents are focused on the problem of representing the environment and its uncertainty in terms of feature based maps. Random Finite Sets are adopted as the fundamental tool to represent a map, and a general framework is proposed for feature management, data association and state estimation. The approaches are tested in a number of experiments on both ground based and marine based facilities.
Download or read book Science Abstracts written by and published by . This book was released on 1995 with total page 1360 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Laser Radar written by National Research Council and published by National Academies Press. This book was released on 2014-03-14 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today's world, the range of technologies with the potential to threaten the security of U.S. military forces is extremely broad. These include developments in explosive materials, sensors, control systems, robotics, satellite systems, and computing power, to name just a few. Such technologies have not only enhanced the capabilities of U.S. military forces, but also offer enhanced offensive capabilities to potential adversaries - either directly through the development of more sophisticated weapons, or more indirectly through opportunities for interrupting the function of defensive U.S. military systems. Passive and active electro-optical (EO) sensing technologies are prime examples. Laser Radar considers the potential of active EO technologies to create surprise; i.e., systems that use a source of visible or infrared light to interrogate a target in combination with sensitive detectors and processors to analyze the returned light. The addition of an interrogating light source to the system adds rich new phenomenologies that enable new capabilities to be explored. This report evaluates the fundamental, physical limits to active EO sensor technologies with potential military utility; identifies key technologies that may help overcome the impediments within a 5-10 year timeframe; considers the pros and cons of implementing each existing or emerging technology; and evaluates the potential uses of active EO sensing technologies, including 3D mapping and multi-discriminate laser radar technologies.
Download or read book Imaging Spectrometry written by Freek D. van der Meer and published by Springer Science & Business Media. This book was released on 2011-03-29 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: A significant step forward in the world of earth observation was made with the development of imaging spectrometry. Imaging spectrometers measure reflected solar radiance from the earth in many narrow spectral bands. Such a spectroscopical imaging system is capable of detecting subtle absorption bands in the reflectance spectra and measure the reflectance spectra of various objects with a very high accuracy. As a result, imaging spectrometry enables a better identification of objects at the earth surface and a better quantification of the object properties than can be achieved by traditional earth observation sensors such as Landsat TM and SPOT. The various chapters in the book present the concepts of imaging spectrometry by discussing the underlying physics and the analytical image processing techniques. The second part of the book presents in detail a wide variety of applications of these new techniques ranging from mineral identification, mapping of expansive soils, land degradation, agricultural crops, natural vegetation and surface water quality. Additional information on extras.springer.com Sample hyperspectral remote sensing data sets and ENVI viewing software (Freelook) are available on http://extras.springer.com
Download or read book Hyperspectral Image Analysis written by Saurabh Prasad and published by Springer Nature. This book was released on 2020-04-27 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas of image analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.
Download or read book International Aerospace Abstracts written by and published by . This book was released on 1998 with total page 920 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Estimation with Applications to Tracking and Navigation written by Yaakov Bar-Shalom and published by John Wiley & Sons. This book was released on 2004-04-05 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: Expert coverage of the design and implementation of state estimation algorithms for tracking and navigation Estimation with Applications to Tracking and Navigation treats the estimation of various quantities from inherently inaccurate remote observations. It explains state estimator design using a balanced combination of linear systems, probability, and statistics. The authors provide a review of the necessary background mathematical techniques and offer an overview of the basic concepts in estimation. They then provide detailed treatments of all the major issues in estimation with a focus on applying these techniques to real systems. Other features include: * Problems that apply theoretical material to real-world applications * In-depth coverage of the Interacting Multiple Model (IMM) estimator * Companion DynaEst(TM) software for MATLAB(TM) implementation of Kalman filters and IMM estimators * Design guidelines for tracking filters Suitable for graduate engineering students and engineers working in remote sensors and tracking, Estimation with Applications to Tracking and Navigation provides expert coverage of this important area.
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1995 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing written by Ni-Bin Chang and published by CRC Press. This book was released on 2018-02-21 with total page 627 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last few years the scientific community has realized that obtaining a better understanding of interactions between natural systems and the man-made environment across different scales demands more research efforts in remote sensing. An integrated Earth system observatory that merges surface-based, air-borne, space-borne, and even underground sensors with comprehensive and predictive capabilities indicates promise for revolutionizing the study of global water, energy, and carbon cycles as well as land use and land cover changes. The aim of this book is to present a suite of relevant concepts, tools, and methods of integrated multisensor data fusion and machine learning technologies to promote environmental sustainability. The process of machine learning for intelligent feature extraction consists of regular, deep, and fast learning algorithms. The niche for integrating data fusion and machine learning for remote sensing rests upon the creation of a new scientific architecture in remote sensing science that is designed to support numerical as well as symbolic feature extraction managed by several cognitively oriented machine learning tasks at finer scales. By grouping a suite of satellites with similar nature in platform design, data merging may come to help for cloudy pixel reconstruction over the space domain or concatenation of time series images over the time domain, or even both simultaneously. Organized in 5 parts, from Fundamental Principles of Remote Sensing; Feature Extraction for Remote Sensing; Image and Data Fusion for Remote Sensing; Integrated Data Merging, Data Reconstruction, Data Fusion, and Machine Learning; to Remote Sensing for Environmental Decision Analysis, the book will be a useful reference for graduate students, academic scholars, and working professionals who are involved in the study of Earth systems and the environment for a sustainable future. The new knowledge in this book can be applied successfully in many areas of environmental science and engineering.
