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Author: Sumedh Puranik
Publisher: LAP Lambert Academic Publishing
ISBN: 9783843364713
Category :
Languages : en
Pages : 188
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Book Description
Target tracking has tremendous applications in both military and civilian surveillance systems. Typical applications are satellite surveillance systems, air-traffic control, undersea surveillance, sophisticated weapon delivery systems, global positioning systems, etc. The rapid developments in hardware and software technology have increased the signal processing capabilities of these surveillance systems. Advances in sensing resources have made possible to collect the enormous and complex amount of observation data from the targets. This has generated a continuing need for further development in information processing capabilities of these systems. Besides that, target tracking is as such a very complex problem. Complexity of the overall tracking problem increases substantially with the presence of maneuvering target, multiple targets, multiple distributed sensors, and background noise or clutter. In this book we develop a set of new suboptimal filtering and smoothing algorithms for maneuvering target tracking application. The proposed algorithms provide better performance in terms of estimation accuracy over the existing algorithms.
Author: Sumedh Puranik
Publisher: LAP Lambert Academic Publishing
ISBN: 9783843364713
Category :
Languages : en
Pages : 188
Get Book Here
Book Description
Target tracking has tremendous applications in both military and civilian surveillance systems. Typical applications are satellite surveillance systems, air-traffic control, undersea surveillance, sophisticated weapon delivery systems, global positioning systems, etc. The rapid developments in hardware and software technology have increased the signal processing capabilities of these surveillance systems. Advances in sensing resources have made possible to collect the enormous and complex amount of observation data from the targets. This has generated a continuing need for further development in information processing capabilities of these systems. Besides that, target tracking is as such a very complex problem. Complexity of the overall tracking problem increases substantially with the presence of maneuvering target, multiple targets, multiple distributed sensors, and background noise or clutter. In this book we develop a set of new suboptimal filtering and smoothing algorithms for maneuvering target tracking application. The proposed algorithms provide better performance in terms of estimation accuracy over the existing algorithms.
Author: Yaakov Bar-Shalom
Publisher:
ISBN:
Category : Radar
Languages : en
Pages : 474
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Book Description
Author: Jun Ye Yu
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
"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." --
Author: Wen-dong Geng
Publisher: Springer
ISBN: 981101888X
Category : Technology & Engineering
Languages : en
Pages : 175
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Book Description
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.
Author: Yaakov Bar-Shalom
Publisher:
ISBN: 9780964831209
Category : Radar
Languages : en
Pages : 615
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Book Description
Author: Mahendra Mallick
Publisher: John Wiley & Sons
ISBN: 0470639059
Category : Technology & Engineering
Languages : en
Pages : 738
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Book Description
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.
Author: Alberto Bemporad
Publisher: Springer Science & Business Media
ISBN: 3540714928
Category : Computers
Languages : en
Pages : 812
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Book Description
This book constitutes the refereed proceedings of the 10th International Conference on Hybrid Systems: Computation and Control, HSCC 2007, held in Pisa, Italy in April 2007. The 44 revised full papers and 39 revised short papers presented together with the abstracts of 3 keynote talks were carefully reviewed and selected from 167 submissions. Among the topics addressed are models of heterogeneous systems, computability and complexity issues, real-time computing and control, embedded and resource-aware control, control and estimation over wireless networks, tools for analysis, verification, control, and design, programming languages support and implementation, applications, including automotive, communication networks, avionics, energy systems, transportation networks, biology and other sciences, manufacturing, and robotics.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 28
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Book Description
A multi-sensor multi-target tracker based on the use of near optimal and real-time algorithms for data association has been developed.
Author: Negm Eldin Mohamed Shawky
Publisher: LAP Lambert Academic Publishing
ISBN: 9783659306938
Category :
Languages : en
Pages : 212
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Book Description
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.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
This report results from a contract tasking Technical University of Crete as follows: I. Construction of a set of problem instances of multidimensional assignment problems in the context of target tracking. These will be used as benchmark problems. They will be constructed so that their optimal solution will be known, and they will vary in size and dimension. Furthermore they will be nontrivial to solve, since they will be used for evaluation of the proposed algorithms in the experimental runs. 2. Design and implementation of data structures to represent the massive sparse data sets associated with each instance of the problem. These data structures will be general enough to handle variable dimension and degrees of sparsity. Specific tasks to be performed by the algorithms, such as function evaluation and construction of feasible and partial solutions, should require minimum computational effort and memory. 3. Design and implementation of heuristic and exact algorithms for solving the multidimensional assignment problem. The heuristic algorithm will receive the dimension of the instance and the sparse multidimensional array as inputs, and it will provide the partitions that represent the targets. The exact algorithm will use a branch-and-bound scheme to provide exact solutions to the problem. All the codes will be written using the C programming language.
