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.

Download or read book Foundations and Applications of Sensor Management written by Alfred Olivier Hero and published by Springer Science & Business Media. This book was released on 2007-10-23 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers control theory signal processing and relevant applications in a unified manner. It introduces the area, takes stock of advances, and describes open problems and challenges in order to advance the field. The editors and contributors to this book are pioneers in the area of active sensing and sensor management, and represent the diverse communities that are targeted.

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.

Download or read book Sensor Management with Applications in Localization and Tracking written by and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, we explore several themes in sensor management with an emphasis on their applications for target localization and tracking. We consider the sensor subset selection problem where a pre-specified number of sensors must be selected in a sensor network to estimate an unknown value of a time-invariant parameter, e.g. the position of a target. We study the Lagrangian and continuous relaxations of this problem with the determinant of the Fisher information matrix as the objective function. We prove that the continuous bound is tighter than the Lagrangian bound and outline an algorithm based on the so-called natural selection process to compute the continuous bound when sensors are allowed to make more than one measurement. We also study how a target can identify the informative sensors when it is facing a network that attempts to estimate its position or its other critical parameters. We show that by borrowing the notion of symmetric probabilistic values from cooperative game theory, the target can assign a power index to each sensor to determine how informative it is relative to the other ones. We further show that by choosing the determinant of the Fisher information matrix as the metric of estimation accuracy, the computational complexity associated with a power index gracefully increases with the number of sensors. Finally, we study the trajectory design problem for bearings-only tracking where the motion of a mobile sensor, called the observer, must be planned in order to estimate the position and the velocity of a moving target via bearing measurements. Our analysis of this problem demonstrates that the optimal solutions can be uniquely specified by only two ratios: (i) The distance that the observer can travel along a straight line during the observation period to the relative distance between the observer and the target. (ii) The speed of the observer relative to the speed of the target.

Download or read book Dynamic Information theoretic Sensor Selection Schemes for Target Tracking Applications written by Farzaneh Razavi Armaghani and published by . This book was released on 2013 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wireless Sensor Networks (WSNs) provide ad hoc infrastructure for the applications that must operate in remote and harsh environments, e.g. target tracking, wildlife tracking, and environmental monitoring. The primary factors driving such pervasive applications are the flexibility, fault tolerance, high sensing fidelity, low cost, and rapid deployment characteristics of WSNs. Energy efficiency is a critical feature of WSNs because sensor nodes run on batteries. Batteries are generally difficult to recharge after deployment. The principal way of increasing the network lifetime is to minimise the number of active sensors in the region of interest.Target tracking applications, being some of the main applications in WSNs, need continuous location estimations of moving objects. The requirement for high accuracy of estimations poses an additional challenge to WSNs. Accuracy of estimations can be improved by activating more sensors. However, this approach to increasing accuracy can result in higher energy consumption and a shorter network lifetime. Therefore, a reliable and effective sensor selection scheme is necessary to rotate the tracking task between the optimal sets of active sensors, to balance the trade-off between estimation accuracy and network lifetime.This thesis addresses the problem of the accuracy-lifetime trade-off in sensor selection, for three types of target tracking applications: single target tracking, multiple-target tracking, and group target tracking. Particle filtering is a widely used Bayesian estimation method that is capable of solving realistic problems. We propose, develop, implement, and validate predictive sensor selection schemes to find the best set of active sensors heuristically. The proposed schemes take advantage of particle filtering to calculate the sensor information utilities based on the predicted locations of targets. The use of sensor information utilities and sensor energy parameters in the design of selection cost metrics facilitates the formation of best sets of active sensors. In addition, the problem of the accuracy-lifetime trade-off deals with the type of data processing mechanism. The proposed schemes investigate the impact of both local and central data processing on the trade-off. Group target tracking applications demand a compatible clustering algorithm to accurately estimate the groups and their constituent targets. The proposed clustering framework adaptively finds the target groups based on the notation of trajectory mining and graph theory, and is incorporated in the design of a region-based sensor selection scheme for group target tracking. To deal with the accuracy-lifetime trade-off, our sensor selection philosophy is to select a dynamic number of sensors at anytime.This thesis presents implementation and evaluation details of the proposed schemes. Extensive simulations and evaluations have been performed to show the energy efficiency of the proposed schemes in accurate tracking of the single, multiple, or grouped targets. The proposed schemes can be applied in different tracking and monitoring applications, e.g. wildlife tracking, environmental monitoring, bushfire tracking, and traffic management. The application is made feasible by redefining the concept of information utility based on the physical property of interest, e.g. sound and temperature. We believe that the adoption of the proposed schemes would assist any tracking application to dynamically reconfigure the sensor activities, so that network lifetime is prolonged and a high quality of information is attained.

Download or read book Sensor Technology Concepts Methodologies Tools and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2020-02-07 with total page 1618 pages. Available in PDF, EPUB and Kindle. Book excerpt: Collecting and processing data is a necessary aspect of living in a technologically advanced society. Whether it’s monitoring events, controlling different variables, or using decision-making applications, it is important to have a system that is both inexpensive and capable of coping with high amounts of data. As the application of these networks becomes more common, it becomes imperative to evaluate their effectiveness as well as other opportunities for possible implementation in the future. Sensor Technology: Concepts, Methodologies, Tools, and Applications is a vital reference source that brings together new ways to process and monitor data and to put it to work in everything from intelligent transportation systems to healthcare to multimedia applications. It also provides inclusive coverage on the processing and applications of wireless communication, sensor networks, and mobile computing. Highlighting a range of topics such as internet of things, signal processing hardware, and wireless sensor technologies, this multi-volume book is ideally designed for research and development engineers, IT specialists, developers, graduate students, academics, and researchers.

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:

Download or read book Adaptive Sensor Management for Target Tracking with Sensor Deployment and Motion Uncertainties written by K. Punithakumar and published by . This book was released on 2003 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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:

Download or read book Tracking and Sensor Data Fusion written by Wolfgang Koch and published by Springer Science & Business Media. This book was released on 2013-09-20 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sensor Data Fusion is the process of combining incomplete and imperfect pieces of mutually complementary sensor information in such a way that a better understanding of an underlying real-world phenomenon is achieved. Typically, this insight is either unobtainable otherwise or a fusion result exceeds what can be produced from a single sensor output in accuracy, reliability, or cost. This book provides an introduction Sensor Data Fusion, as an information technology as well as a branch of engineering science and informatics. Part I presents a coherent methodological framework, thus providing the prerequisites for discussing selected applications in Part II of the book. The presentation mirrors the author's views on the subject and emphasizes his own contributions to the development of particular aspects. With some delay, Sensor Data Fusion is likely to develop along lines similar to the evolution of another modern key technology whose origin is in the military domain, the Internet. It is the author's firm conviction that until now, scientists and engineers have only scratched the surface of the vast range of opportunities for research, engineering, and product development that still waits to be explored: the Internet of the Sensors.

Download or read book Theory and Algorithms for Cooperative Systems written by Don Grundel and published by World Scientific. This book was released on 2004 with total page 603 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past several years, cooperative control and optimization have increasingly played a larger and more important role in many aspects of military sciences, biology, communications, robotics, and decision making. At the same time, cooperative systems are notoriously difficult to model, analyze, and solve — while intuitively understood, they are not axiomatically defined in any commonly accepted manner. The works in this volume provide outstanding insights into this very complex area of research. They are the result of invited papers and selected presentations at the Fourth Annual Conference on Cooperative Control and Optimization held in Destin, Florida, November 2003.This book has been selected for coverage in: • Index to Scientific & Technical Proceedings® (ISTP® / ISI Proceedings)• Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings)• CC Proceedings — Engineering & Physical Sciences

Download or read book Probabilistic Framework for Sensor Management written by Marco Huber and published by KIT Scientific Publishing. This book was released on 2009 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: A probabilistic sensor management framework is introduced, which maximizes the utility of sensor systems with many different sensing modalities by dynamically configuring the sensor system in the most beneficial way. For this purpose, techniques from stochastic control and Bayesian estimation are combined such that long-term effects of possible sensor configurations and stochastic uncertainties resulting from noisy measurements can be incorporated into the sensor management decisions.

Download or read book Management of Target tracking Sensor Networks written by Khaled Hadi and published by . This book was released on 2009 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Adaptive Sensing for Target Tracking Applications written by Aashish Poudel and published by . This book was released on 2011 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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.

Download or read book Information Processing in Sensor Networks written by Feng Zhao and published by Springer Science & Business Media. This book was released on 2003-04-10 with total page 688 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Workshop on Information Processing in Sensor Networks, IPSN 2003, held in Palo Alto, CA, USA, in April 2003. The 23 revised full papers and 21 revised poster papers presented were carefully reviewed and selected from 73 submissions. Among the topics addressed are wireless sensor networks, query processing, decentralized sensor platforms, distributed databases, distributed group management, sensor network design, collaborative signal processing, adhoc sensor networks, distributed algorithms, distributed sensor network control, sensor network resource management, data service middleware, random sensor networks, mobile agents, target tracking, sensor network protocols, large scale sensor networks, and multicast.

Download or read book Advances in Multi Sensor Information Fusion Theory and Applications 2017 written by Xue-Bo Jin and published by MDPI. This book was released on 2018-06-26 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Advances in Multi-Sensor Information Fusion: Theory and Applications 2017" that was published in Sensors