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 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:
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 Multitarget multisensor Tracking written by Yaakov Bar-Shalom and published by . This book was released on 1990 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multitarget multisensor Tracking written by Yaakov Bar-Shalom and published by . This book was released on 1990 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multitarget multisensor Tracking written by Yaakov Bar-Shalom and published by Artech House Publishers. This book was released on 1990 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multitarget multisensor Tracking written by and published by . This book was released on 1990 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multisensor Decision And Estimation Fusion written by Yunmin Zhu and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: YUNMIN ZHU In the past two decades, multi sensor or multi-source information fusion tech niques have attracted more and more attention in practice, where observations are processed in a distributed manner and decisions or estimates are made at the individual processors, and processed data (or compressed observations) are then transmitted to a fusion center where the final global decision or estimate is made. A system with multiple distributed sensors has many advantages over one with a single sensor. These include an increase in the capability, reliability, robustness and survivability of the system. Distributed decision or estimation fusion prob lems for cases with statistically independent observations or observation noises have received significant attention (see Varshney's book Distributed Detec tion and Data Fusion, New York: Springer-Verlag, 1997, Bar-Shalom's book Multitarget-Multisensor Tracking: Advanced Applications, vol. 1-3, Artech House, 1990, 1992,2000). Problems with statistically dependent observations or observation noises are more difficult and have received much less study. In practice, however, one often sees decision or estimation fusion problems with statistically dependent observations or observation noises. For instance, when several sensors are used to detect a random signal in the presence of observation noise, the sensor observations could not be statistically independent when the signal is present. This book provides a more complete treatment of the fundamentals of multi sensor decision and estimation fusion in order to deal with general random ob servations or observation noises that are correlated across the sensors.
Download or read book Multitarget Multisensor Tracking for Data Fusion written by Sungshin Kwak and published by . This book was released on 2000 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optimization Problems in Multitarget Multisensor Tracking written by and published by . This book was released on 1995 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: A multi-sensor multi-target tracker based on the use of near optimal and real-time algorithms for data association has been developed.
Download or read book Estimation and Multitarget multisensor Tracking Principles and Techniques written by and published by . This book was released on 1990 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multitarget Multisensor Tracking written by Santosh Nannuru and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "In this thesis we develop various multitarget tracking algorithms that can process measurements from single or multiple sensors. The filters are derived by approximate application of the recursive Bayes filter within the random finite set framework, which is used to model the multitarget state and observations. The contributions of the thesis can be organized into three main categories.To provide a motivating application for the algorithms we develop, we first study the problem of radio frequency tomography. We empirically validate a radio frequency tomography measurement model when multiple targets are present within the sensor network. We validate modelsfor both indoor and outdoor environments. These models are then used to perform multitarget tracking using various Monte Carlo filters on data gathered from field deployments of radio frequency sensor networks.Second, we develop auxiliary particle filter implementations of the Probability Hypothesis Density filter and Cardinalized Probability Hypothesis Density filter when the measurement model has a specific form, namely the superpositional sensor model. We also derive Multi-Bernoulli filter and Hybrid Multi-Bernoulli Cardinalized Probability Hypothesis Density filter for superpositional sensors and develop their auxiliary particle filter implementations. These filters are evaluated for multitarget tracking using simulated radio frequency tomography and acoustic sensor network models.Third, we derive update equations for the General Multisensor Cardinalized Probability Hypothesis Density filter when the measurement model has a specific form, namely the standard sensor model. To overcome the combinatorial computational complexity of this filter we develop a Gaussian mixture model-based greedy algorithmto implement the filter in a computationally tractable manner. The filter is evaluated using simulated multisensor measurements." --
Download or read book Multi Sensor Data Fusion with MATLAB written by Jitendra R. Raol and published by CRC Press. This book was released on 2009-12-16 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using MATLAB examples wherever possible, Multi-Sensor Data Fusion with MATLAB explores the three levels of multi-sensor data fusion (MSDF): kinematic-level fusion, including the theory of DF; fuzzy logic and decision fusion; and pixel- and feature-level image fusion. The authors elucidate DF strategies, algorithms, and performance evaluation mainly
Download or read book Advances in Multitarget Multisensor Tracking written by L. Chisci and published by . This book was released on 2010 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: This booklet explores the applicability of the random set approach to the field of multitarget multisensor tracking; the random set approach regards both targets and measurements as random finite sets, i.e. objects in which randomness is not only in the assumed values but also in the number of elements.
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.
Download or read book Multitarget Multisensor Tracking Problems Part 1 A General Solution and a Unified View on Bayesian Approaches written by Shozo Mori and published by . This book was released on 1984 with total page 69 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based upon a general target sensor model which allows dependence among targets and state-dependent target detection, a Bayesian solution to the multitarget tracking problem is derived. When this solution is applied to a special class of models, a less general but more implementationally feasible class of algorithms is obtained. Representative existing algorithms are then compared with our results. Doing so provides a unified view on Bayesian approaches to the multitarget tracking problem. Part I covers most of the analytical results, while in Part II, hypothesis management and other issues pertaining to implementation of multitarget algorithms are discussed with several examples. (jd/rh).
Download or read book Advances in Statistical Multisource Multitarget Information Fusion written by Ronald P.S. Mahler and published by Artech House. This book was released on 2014-08-01 with total page 1167 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the sequel to the 2007 Artech House bestselling title, Statistical Multisource-Multitarget Information Fusion. That earlier book was a comprehensive resource for an in-depth understanding of finite-set statistics (FISST), a unified, systematic, and Bayesian approach to information fusion. The cardinalized probability hypothesis density (CPHD) filter, which was first systematically described in the earlier book, has since become a standard multitarget detection and tracking technique, especially in research and development. Since 2007, FISST has inspired a considerable amount of research, conducted in more than a dozen nations, and reported in nearly a thousand publications. This sequel addresses the most intriguing practical and theoretical advances in FISST, for the first time aggregating and systematizing them into a coherent, integrated, and deep-dive picture. Special emphasis is given to computationally fast exact closed-form implementation approaches. The book also includes the first complete and systematic description of RFS-based sensor/platform management and situation assessment.