Single Object Detection Using Multiple Sensors With Unknown Noise Distributions
DOWNLOAD
Download Single Object Detection Using Multiple Sensors With Unknown Noise Distributions PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Single Object Detection Using Multiple Sensors With Unknown Noise Distributions book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Single Object Detection Using Multiple Sensors With Unknown Noise Distributions
DOWNLOAD
Author : Shaofen Chen
language : en
Publisher:
Release Date : 1992
Single Object Detection Using Multiple Sensors With Unknown Noise Distributions written by Shaofen Chen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Distributed operating systems (Computers) categories.
Random Finite Set Information Theoretic Sensor Control For Autonomous Multi Sensor Multi Object Surveillance
DOWNLOAD
Author : Keith Allen LeGrand
language : en
Publisher:
Release Date : 2022
Random Finite Set Information Theoretic Sensor Control For Autonomous Multi Sensor Multi Object Surveillance written by Keith Allen LeGrand and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
Tracking multiple moving objects in complex environments is a key objective of many robotic and aerospace surveillance systems. In the Bayesian multi-object tracking framework, noisy sensor measurements are assimilated over time to form probabilistic beliefs, namely probability densities, of the multi-object state by virtue of Bayes' rule. This dissertation shows that, using probabilistic beliefs and environmental feedback, intelligent sensors can also optimize the value of information gathered in real time by means of information-driven control. In particular, it is shown that in object tracking applications, sensor actions can be optimized based on the expected reduction in uncertainty or information gain estimated from probabilistic beliefs for future sensor measurements. When compared to traditional estimation problems, the problem of estimating the information value for multi-object surveillance is more challenging due to unknown object-measurement association and unknown object existence. The advent of random finite set (RFS) theory has provided a formalism for quantifying and estimating information gain in multi-object tracking problems. However, direct computation of many relevant RFS functions, including posterior density functions and predicted information gain functions, is often intractable and requires principled approximation. This dissertation presents new theory, approximations, and algorithms related to autonomous multi-sensor multi-object surveillance. A new approach is presented for systematically incorporating ambiguous inclusion/exclusion type evidence, such as the non-detection of an object within a known sensor field-of-view (FoV). The resulting state estimation problem is nonlinear and solved using a new Gaussian mixture approximation achieved through recursive component splitting.Based on this approximation, a novel Gaussian mixture Bernoulli filter for imprecise measurements is derived. The filter can accommodate "soft" data from human sources and is demonstrated in a tracking problem using only natural language statements as inputs. This dissertation further investigates the relationship between bounded FoVs and cardinality distributions for a representative selection of multi-object distributions. These new FoV cardinality distributions can be used for sensor planning, as is demonstrated through a problem involving a multi-Bernoulli process with up to one hundred potential objects. Finally, a new tractable approximation is presented for RFS expected information gain that is applicable to sensor control in multi-sensor multi-object search-while-tracking problems. Unlike existing RFS approaches, the approximation presented in this dissertation accounts for multiple measurement outcomes due to noise, missed detections, false alarms, and object appearance/disappearance. The effectiveness of the information-driven sensor control is demonstrated through a multi-vehicle search-while-tracking experiment using real video data from a remote optical sensor.
Stochastic Large Scale Engineering Systems
DOWNLOAD
Author : Spyros G. Tzafestas
language : en
Publisher: CRC Press
Release Date : 2020-08-18
Stochastic Large Scale Engineering Systems written by Spyros G. Tzafestas and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-18 with Technology & Engineering categories.
This book focuses on the class of large-scale stochastic systems, which has dominated the attention of many academic and research groups. It discusses distributed-sensor networks, decentralized detection theory, and econometric models with integrated and decentralized policymakers.
Grid Based Nonlinear Estimation And Its Applications
DOWNLOAD
Author : Bin Jia
language : en
Publisher: CRC Press
Release Date : 2019-04-25
Grid Based Nonlinear Estimation And Its Applications written by Bin Jia and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-25 with Mathematics categories.
Grid-based Nonlinear Estimation and its Applications presents new Bayesian nonlinear estimation techniques developed in the last two decades. Grid-based estimation techniques are based on efficient and precise numerical integration rules to improve performance of the traditional Kalman filtering based estimation for nonlinear and uncertainty dynamic systems. The unscented Kalman filter, Gauss-Hermite quadrature filter, cubature Kalman filter, sparse-grid quadrature filter, and many other numerical grid-based filtering techniques have been introduced and compared in this book. Theoretical analysis and numerical simulations are provided to show the relationships and distinct features of different estimation techniques. To assist the exposition of the filtering concept, preliminary mathematical review is provided. In addition, rather than merely considering the single sensor estimation, multiple sensor estimation, including the centralized and decentralized estimation, is included. Different decentralized estimation strategies, including consensus, diffusion, and covariance intersection, are investigated. Diverse engineering applications, such as uncertainty propagation, target tracking, guidance, navigation, and control, are presented to illustrate the performance of different grid-based estimation techniques.
Distributed Detection From Multiple Sensors With Correlated Observations
DOWNLOAD
Author : Yawgeng A. Chau
language : en
Publisher:
Release Date : 1989
Distributed Detection From Multiple Sensors With Correlated Observations written by Yawgeng A. Chau and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with Detectors categories.
Multi Sensor Imaging And Fusion Methods Evaluations And Applications
DOWNLOAD
Author : Zhiqin Zhu
language : en
Publisher: Frontiers Media SA
Release Date : 2023-10-25
Multi Sensor Imaging And Fusion Methods Evaluations And Applications written by Zhiqin Zhu and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-25 with Science categories.
Scientific And Technical Aerospace Reports
DOWNLOAD
Author :
language : en
Publisher:
Release Date : 1995
Scientific And Technical Aerospace Reports written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Aeronautics categories.
Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
Integrated Tracking Classification And Sensor Management
DOWNLOAD
Author : Mahendra Mallick
language : en
Publisher: John Wiley & Sons
Release Date : 2012-11-05
Integrated Tracking Classification And Sensor Management written by Mahendra Mallick and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-05 with Technology & Engineering categories.
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.
Distributed Video Sensor Networks
DOWNLOAD
Author : Bir Bhanu
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-01-04
Distributed Video Sensor Networks written by Bir Bhanu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-04 with Computers categories.
Large-scale video networks are of increasing importance in a wide range of applications. However, the development of automated techniques for aggregating and interpreting information from multiple video streams in real-life scenarios is a challenging area of research. Collecting the work of leading researchers from a broad range of disciplines, this timely text/reference offers an in-depth survey of the state of the art in distributed camera networks. The book addresses a broad spectrum of critical issues in this highly interdisciplinary field: current challenges and future directions; video processing and video understanding; simulation, graphics, cognition and video networks; wireless video sensor networks, communications and control; embedded cameras and real-time video analysis; applications of distributed video networks; and educational opportunities and curriculum-development. Topics and features: presents an overview of research in areas of motion analysis, invariants, multiple cameras for detection, object tracking and recognition, and activities in video networks; provides real-world applications of distributed video networks, including force protection, wide area activities, port security, and recognition in night-time environments; describes the challenges in graphics and simulation, covering virtual vision, network security, human activities, cognitive architecture, and displays; examines issues of multimedia networks, registration, control of cameras (in simulations and real networks), localization and bounds on tracking; discusses system aspects of video networks, with chapters on providing testbed environments, data collection on activities, new integrated sensors for airborne sensors, face recognition, and building sentient spaces; investigates educational opportunities and curriculum development from the perspective of computer science and electrical engineering. This unique text will be of great interest to researchers and graduate students of computer vision and pattern recognition, computer graphics and simulation, image processing and embedded systems, and communications, networks and controls. The large number of example applications will also appeal to application engineers.
Parallel And Distributed Signal And Image Integration Problems Proceedings Of The Indo Us Workshop
DOWNLOAD
Author : Rabinder N Madan
language : en
Publisher: World Scientific
Release Date : 1995-06-09
Parallel And Distributed Signal And Image Integration Problems Proceedings Of The Indo Us Workshop written by Rabinder N Madan and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-06-09 with categories.
The next generation of engineering and computing systems will be both complex and distributed in functionality due to a variety of information sources needed for their operation. Successful development and deployment of these systems critically depends on the mechanisms for acquisition, coordination, communication and integration of information from various components. This collection of papers addresses various aspects in the area of signal and image integration with a specific emphasis on parallel and distributed solutions. A wide spectrum of issues including image and signal processing, parallel architectures/algorithms, sensor integration/fusion, and neural networks/fuzzy systems, are addressed in various papers.