Handbook of multisensor data fusion theory and practice
In the years since the bestselling first edition, fusion research and applications have adapted to service-oriented architectures and pushed the boundaries of situational modeling in human behavior, expanding into fields such as chemical and biological sensing, crisis management, and intelligent bui...
| Other Authors: | , , |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
Boca Raton, FL
CRC Press
2009
|
| Edition: | Second edition |
| Series: | The electrical engineering and applied signal processing series
|
| Subjects: | |
| Online Access: | |
| Collection: | O'Reilly - Collection details see MPG.ReNa |
Table of Contents:
- Distributed fusion architectures, algorithms, and performance within a network-centric architecture
- Foundations of situation and threat assessment
- Introduction to level 5 fusion : the role of the user
- Perspectives on the human side of data fusion : prospects for improved effectiveness using advanced human-computer interfaces
- Requirements derivation for data fusion systems
- Systems engineering approach for implementing data fusion systems
- Studies and analyses within project correlation : an in-depth assessment of correlation problems and solution techniques
- Data management support to tactical data fusion
- Assessing the performance of multisensor fusion processes
- Survey of COTS software for multisensor data fusion
- Survey of multisensor data fusion systems
- Data fusion for developing predictive diagnostics for electromechanical systems
- Adapting data fusion to chemical and biological sensors
- Includes bibliographical references and index
- Multisensor data fusion Data fusion perspectives and its role in information processing
- Revisions to the JDL data fusion model
- Introduction to the algorithmics of data association in multiple-target tracking
- Principles and practice of image and spatial data fusion
- Data registration
- Data fusion automation : a top-down perspective
- Overview of distributed decision fusion
- Introduction to particle filtering : the next stage in tracking
- Target tracking using probabilistic data association-based techniques with applications to sonar, radar, and EO sensors
- Introduction to the combinatorics of optimal and approximate data association
- Bayesian approach to multiple-target tracking
- Data association using multiple-frame assignments
- General decentralized data fusion with covariance intersection
- Data fusion in nonlinear systems
- Random set theory for multisource-multitarget information fusion
- Fusion of ground and satellite data via Army battle command systems
- Developing information fusion methods for combat identification