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Optimum Techniques Multi Sensor Multi Target Tracking And Track Association
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Book Synopsis Optimum Techniques Multi-sensor Multi-target Tracking and Track Association by : Evangelos H. Giannopoulos
Download or read book Optimum Techniques Multi-sensor Multi-target Tracking and Track Association written by Evangelos H. Giannopoulos and published by . This book was released on 1999 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Multitarget-multisensor Tracking by : Yaakov Bar-Shalom
Download or read book Multitarget-multisensor Tracking written by Yaakov Bar-Shalom and published by . This book was released on 1995 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Sensor Management for Target Tracking Applications by : Per Boström-Rost
Download or read book Sensor Management for Target Tracking Applications written by Per Boström-Rost and published by Linköping University Electronic Press. This book was released on 2021-04-12 with total page 61 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many practical applications, such as search and rescue operations and environmental monitoring, involve the use of mobile sensor platforms. The workload of the sensor operators is becoming overwhelming, as both the number of sensors and their complexity are increasing. This thesis addresses the problem of automating sensor systems to support the operators. This is often referred to as sensor management. By planning trajectories for the sensor platforms and exploiting sensor characteristics, the accuracy of the resulting state estimates can be improved. The considered sensor management problems are formulated in the framework of stochastic optimal control, where prior knowledge, sensor models, and environment models can be incorporated. The core challenge lies in making decisions based on the predicted utility of future measurements. In the special case of linear Gaussian measurement and motion models, the estimation performance is independent of the actual measurements. This reduces the problem of computing sensing trajectories to a deterministic optimal control problem, for which standard numerical optimization techniques can be applied. A theorem is formulated that makes it possible to reformulate a class of nonconvex optimization problems with matrix-valued variables as convex optimization problems. This theorem is then used to prove that globally optimal sensing trajectories can be computed using off-the-shelf optimization tools. As in many other fields, nonlinearities make sensor management problems more complicated. Two approaches are derived to handle the randomness inherent in the nonlinear problem of tracking a maneuvering target using a mobile range-bearing sensor with limited field of view. The first approach uses deterministic sampling to predict several candidates of future target trajectories that are taken into account when planning the sensing trajectory. This significantly increases the tracking performance compared to a conventional approach that neglects the uncertainty in the future target trajectory. The second approach is a method to find the optimal range between the sensor and the target. Given the size of the sensor's field of view and an assumption of the maximum acceleration of the target, the optimal range is determined as the one that minimizes the tracking error while satisfying a user-defined constraint on the probability of losing track of the target. While optimization for tracking of a single target may be difficult, planning for jointly maintaining track of discovered targets and searching for yet undetected targets is even more challenging. Conventional approaches are typically based on a traditional tracking method with separate handling of undetected targets. Here, it is shown that the Poisson multi-Bernoulli mixture (PMBM) filter provides a theoretical foundation for a unified search and track method, as it not only provides state estimates of discovered targets, but also maintains an explicit representation of where undetected targets may be located. Furthermore, in an effort to decrease the computational complexity, a version of the PMBM filter which uses a grid-based intensity to represent undetected targets is derived.
Book Synopsis Multi-sensor Multi-target Data Fusion, Tracking and Identification Techniques for Guidance and Control Applications by :
Download or read book Multi-sensor Multi-target Data Fusion, Tracking and Identification Techniques for Guidance and Control Applications written by and published by . This book was released on 1996 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Resumé på fransk.
Book Synopsis Optimization Problems in Multitarget/Multisensor Tracking by :
Download or read book Optimization Problems in Multitarget/Multisensor Tracking written by and published by . This book was released on 1997 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ever-increasing demand in surveillance is to produce highly accurate target and track identification and estimation in real-time, even for dense target scenarios and in regions of high track contention. The use of multiple sensors, through more varied information, has the potential to greatly enhance target identification and state estimation. For multitarget tracking, the processing of multiple scans all at once yields the desired track identification and accurate state estimation; however, one must solve an NP-hard data association problem of partitioning observations into tracks and false alarms in real-time. This report summarizes the development of a multisensor-multitarget tracker based on the use of near-optimal and real-time algorithms for the data association problem and is divided into several parts. The first part addresses the formulation of multisensor and multiscan processing of the data association problem as a combinatorial optimization problem. The new algorithms under development for this NP-hard problem are based on a recursive Lagrangian relaxation scheme, construct near-optimal solutions in real-time, and use a variety of techniques such as two-dimensional assignment algorithms, a bundle trust region method for the nonsmooth optimization, and graph theoretic algorithms for problem decomposition. A brief computational complexity analysis as well as a comparison with some additional heuristic and optimal algorithms is included to demonstrate the efficiency of the algorithms. New results on numerical efficiency and increased robustness for track maintenance are also discussed. This program has produced two U.S. patents with a third pending and has developed the basis for the IBest of Breed Tracker Contest winner at Hanscom AFB in 1996.
Book Synopsis Group-target Tracking by : Wen-dong Geng
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.
Book Synopsis Multitarget-multisensor Tracking: Applications and advances by : Yaakov Bar-Shalom
Download or read book Multitarget-multisensor Tracking: Applications and advances written by Yaakov Bar-Shalom and published by . This book was released on 1990 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Integrated Tracking, Classification, and Sensor Management by : Mahendra Mallick
Download or read book Integrated Tracking, Classification, and Sensor Management written by Mahendra Mallick and published by John Wiley & Sons. This book was released on 2012-12-03 with total page 738 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unique guide to the state of the art of tracking, classification, and sensor management This book addresses the tremendous progress made over the last few decades in algorithm development and mathematical analysis for filtering, multi-target multi-sensor tracking, sensor management and control, and target classification. It provides for the first time an integrated treatment of these advanced topics, complete with careful mathematical formulation, clear description of the theory, and real-world applications. Written by experts in the field, Integrated Tracking, Classification, and Sensor Management provides readers with easy access to key Bayesian modeling and filtering methods, multi-target tracking approaches, target classification procedures, and large scale sensor management problem-solving techniques. Features include: An accessible coverage of random finite set based multi-target filtering algorithms such as the Probability Hypothesis Density filters and multi-Bernoulli filters with focus on problem solving A succinct overview of the track-oriented MHT that comprehensively collates all significant developments in filtering and tracking A state-of-the-art algorithm for hybrid Bayesian network (BN) inference that is efficient and scalable for complex classification models New structural results in stochastic sensor scheduling and algorithms for dynamic sensor scheduling and management Coverage of the posterior Cramer-Rao lower bound (PCRLB) for target tracking and sensor management Insight into cutting-edge military and civilian applications, including intelligence, surveillance, and reconnaissance (ISR) With its emphasis on the latest research results, Integrated Tracking, Classification, and Sensor Management is an invaluable guide for researchers and practitioners in statistical signal processing, radar systems, operations research, and control theory.
Book Synopsis Optimization Problems in Multisensor and Multitarget Tracking by :
Download or read book Optimization Problems in Multisensor and Multitarget Tracking written by and published by . This book was released on 2008 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this research program is to develop optimization algorithms that solve key problems in multiple target tracking and sensor data fusion. The central problem in multiple target tracking is the data association problem of partitioning sensor reports into tracks and false alarms. New classes of data association problems have been formulated and initial algorithms developed to address cluster tracking, merged measurements, and even sensor resource management in the form of "group-assignments." In a different direction, an efficient k-best algorithm has been developed to approximate the uncertainty in data association, which is ontical for discrimination or combat identification. Statistical Monte Carlo methods are also applicable and are still under investigation. Bias estimation algorithms using known data association such as truth objects and targets of opportunity have been developed. Bias estimation in which data association is unknown is difficult due to the nonconvex and mixed integer nature of the mathematical formulation. Exact and approximate algorithms have been developed and successfully applied to system tracking. As a prerequisite to the development of multiple target tracking approaches to space surveillance, consistent measures of uncertainty for initial orbit determination and the propagation of the uncertainty over time have been developed.
Book Synopsis Multisensor Fusion by : Anthony K. Hyder
Download or read book Multisensor Fusion written by Anthony K. Hyder and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 929 pages. Available in PDF, EPUB and Kindle. Book excerpt: For some time, all branches of the military have used a wide range of sensors to provide data for many purposes, including surveillance, reconnoitring, target detection and battle damage assessment. Many nations have also attempted to utilise these sensors for civilian applications, such as crop monitoring, agricultural disease tracking, environmental diagnostics, cartography, ocean temperature profiling, urban planning, and the characterisation of the Ozone Hole above Antarctica. The recent convergence of several important technologies has made possible new, advanced, high performance, sensor based applications relying on the near-simultaneous fusion of data from an ensemble of different types of sensors. The book examines the underlying principles of sensor operation and data fusion, the techniques and technologies that enable the process, including the operation of 'fusion engines'. Fundamental theory and the enabling technologies of data fusion are presented in a systematic and accessible manner. Applications are discussed in the areas of medicine, meteorology, BDA and targeting, transportation, cartography, the environment, agriculture, and manufacturing and process control.
Book Synopsis Multi-Camera Networks by : Hamid Aghajan
Download or read book Multi-Camera Networks written by Hamid Aghajan and published by Academic Press. This book was released on 2009-04-25 with total page 623 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first book, by the leading experts, on this rapidly developing field with applications to security, smart homes, multimedia, and environmental monitoring Comprehensive coverage of fundamentals, algorithms, design methodologies, system implementation issues, architectures, and applications Presents in detail the latest developments in multi-camera calibration, active and heterogeneous camera networks, multi-camera object and event detection, tracking, coding, smart camera architecture and middleware This book is the definitive reference in multi-camera networks. It gives clear guidance on the conceptual and implementation issues involved in the design and operation of multi-camera networks, as well as presenting the state-of-the-art in hardware, algorithms and system development. The book is broad in scope, covering smart camera architectures, embedded processing, sensor fusion and middleware, calibration and topology, network-based detection and tracking, and applications in distributed and collaborative methods in camera networks. This book will be an ideal reference for university researchers, R&D engineers, computer engineers, and graduate students working in signal and video processing, computer vision, and sensor networks. Hamid Aghajan is a Professor of Electrical Engineering (consulting) at Stanford University. His research is on multi-camera networks for smart environments with application to smart homes, assisted living and well being, meeting rooms, and avatar-based communication and social interactions. He is Editor-in-Chief of Journal of Ambient Intelligence and Smart Environments, and was general chair of ACM/IEEE ICDSC 2008. Andrea Cavallaro is Reader (Associate Professor) at Queen Mary, University of London (QMUL). His research is on target tracking and audiovisual content analysis for advanced surveillance and multi-sensor systems. He serves as Associate Editor of the IEEE Signal Processing Magazine and the IEEE Trans. on Multimedia, and has been general chair of IEEE AVSS 2007, ACM/IEEE ICDSC 2009 and BMVC 2009. The first book, by the leading experts, on this rapidly developing field with applications to security, smart homes, multimedia, and environmental monitoring Comprehensive coverage of fundamentals, algorithms, design methodologies, system implementation issues, architectures, and applications Presents in detail the latest developments in multi-camera calibration, active and heterogeneous camera networks, multi-camera object and event detection, tracking, coding, smart camera architecture and middleware
Book Synopsis Advanced Data Association Techniques in Multi-target Tracking System by : Negm Eldin Mohamed Shawky
Download or read book Advanced Data Association Techniques in Multi-target Tracking System written by Negm Eldin Mohamed Shawky and published by LAP Lambert Academic Publishing. This book was released on 2012 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: In multi-target tracking system, data association and tracking filter are two basic parts of tracking objects. The choosing of data association technique to associate the track to the true target in noisy received measurements is an important key to overcome the issues of the tracking process. Many data association algorithms have been developed to be the most powerful techniques for these issues, but still there are disadvantages in their restricting assumptions, complexity and in the resulting performance. For these reasons, some of data association algorithms that are widely used have been studied. These algorithms have some issues during tracking in dense clutter environment, tracking a highly maneuvering targets and swapping in the presence of more background clutter and false signal. Then, these algorithms have been updated to overcome the issues, improve the performance, decrease the burden of the computational cost, decrease the probability of error and to give the targets the ability to continue tracking without failing.
Book Synopsis MULTI-SENSOR MULTI-TARGET DATA FUSION, TRACKING AND IDENTIFICATION TECHNIQUES FOR GUIDANCE AND CONTROL APPLICATIONS. by : North Atlantic Treaty Organization
Download or read book MULTI-SENSOR MULTI-TARGET DATA FUSION, TRACKING AND IDENTIFICATION TECHNIQUES FOR GUIDANCE AND CONTROL APPLICATIONS. written by North Atlantic Treaty Organization and published by . This book was released on 1996 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Multi-sensor Target Tracking by : Jun Ye Yu
Download or read book Multi-sensor Target Tracking written by Jun Ye Yu and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Target tracking is a well-studied research topic with a vast array of applications. The basic idea is to track one or more targets of interest using data collected by one or more sensors. While a single sensor may provide enough data, it is more beneficial to establish a network of sensors that collaborate with each other. In this thesis, we study multi-sensor target tracking and present three manuscripts.In the first manuscript, we present a distributed bearings-only single-target particle filter. Unlike the existing literature, the proposed filter incorporates the Earth's curvature in the measurement model to provide more accurate bearing computation. Furthermore, we derive an approximate joint log-likelihood function to reduce the total communication overhead. In the second manuscript, we extend our work in the first manuscript and present two compression algorithms for distributed particle filters. The proposed algorithms construct a graph over the particles and exploit the resulting graph Laplacian matrix to encode the particle log-likelihoods. The proposed algorithms are not limited to any measurement models and can be incorporated in any generic particle filter. We also derive theoretical results showing that the proposed algorithms outperform existing methods at low communication overhead. In the third manuscript, we study data assignment in multi-target tracking. We propose two heuristic but computationally efficient algorithms for multi-sensor multi-target data assignment that can generate a number of likely target-measurement associations. We also implement these algorithms in a generalized labeled multi-Bernoulli filter to validate their performance." --
Book Synopsis Multi-Sensor Information Fusion by : Xue-Bo Jin
Download or read book Multi-Sensor Information Fusion written by Xue-Bo Jin and published by MDPI. This book was released on 2020-03-23 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes papers from the section “Multisensor Information Fusion”, from Sensors between 2018 to 2019. It focuses on the latest research results of current multi-sensor fusion technologies and represents the latest research trends, including traditional information fusion technologies, estimation and filtering, and the latest research, artificial intelligence involving deep learning.
Book Synopsis Multisensor Data Association and Resource Management for Target Tracking by : Thiagalingam Kirubarajan
Download or read book Multisensor Data Association and Resource Management for Target Tracking written by Thiagalingam Kirubarajan and published by . This book was released on 1998 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Target Tracking with Random Finite Sets by : Weihua Wu
Download or read book Target Tracking with Random Finite Sets written by Weihua Wu and published by Springer Nature. This book was released on 2023-08-02 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on target tracking and information fusion with random finite sets. Both principles and implementations have been addressed, with more weight placed on engineering implementations. This is achieved by providing in-depth study on a number of major topics such as the probability hypothesis density (PHD), cardinalized PHD, multi-Bernoulli (MB), labeled MB (LMB), d-generalized LMB (d-GLMB), marginalized d-GLMB, together with their Gaussian mixture and sequential Monte Carlo implementations. Five extended applications are covered, which are maneuvering target tracking, target tracking for Doppler radars, track-before-detect for dim targets, target tracking with non-standard measurements, and target tracking with multiple distributed sensors. The comprehensive and systematic summarization in target tracking with RFSs is one of the major features of the book, which is particularly suited for readers who are interested to learn solutions in target tracking with RFSs. The book benefits researchers, engineers, and graduate students in the fields of random finite sets, target tracking, sensor fusion/data fusion/information fusion, etc.
