Sciyo, 2010, — 494 p. — ISBN: 978-953-307-101-5.The idea of this book on Sensor fusion and its Applications comes as a response to the immense interest and strong activities in the field of sensor fusion. Sensor fusion represents a topic of interest from both theoretical and practical perspectives.
The technology of sensor fusion combines pieces of information coming from different sources/sensors, resulting in an enhanced overall system performance with respect to separate sensors/sources. Different sensor fusion methods have been developed in order to optimize the overall system output in a variety of applications for which sensor fusion might be useful: sensor networks, security, medical diagnosis, navigation, biometrics, environmental monitoring, remote sensing, measurements, robotics, etc. Variety of techniques, architectures, levels, etc., of sensor fusion enables to bring solutions in various areas of diverse disciplines.
This book aims to explore the latest practices and research works in the area of sensor fusion. The book intends to provide a collection of novel ideas, theories, and solutions related to the research areas in the field of sensor fusion. This book aims to satisfy the needs of researchers, academics, and practitioners working in the field of sensor fusion. This book is a unique, comprehensive, and up-to-date resource for sensor fusion systems designers. This book is appropriate for use as an upper division undergraduate or graduate level text book. It should also be of interest to researchers, who need to process and interpret the sensor data in most scientific and engineering fields.
Initial chapters in this book provide a general overview of sensor fusion. The later chapters focus mostly on the applications of sensor fusion. Much of this work has been published in refereed journals and conference proceedings and these papers have been modified and edited for content and style. With contributions from the world’s leading fusion researchers and academicians, this book has 22 chapters covering the fundamental theory and cuttingedge developments that are driving this field.State Optimal Estimation for Nonstandard Multi-sensor Information Fusion System.
Air traffic trajectories segmentation based on time-series sensor data.
Distributed Compressed Sensing of Sensor Data.
Adaptive Kalman Filter for Navigation Sensor Fusion.
Fusion of Images Recorded with Variable Illumination.
Camera and laser robust integration in engineering and architecture applications.
Spatial Voting With Data Modeling.
Hidden Markov Model as a Framework for Situational Awareness.
Multi-sensorial Active Perception for Indoor Environment Modeling.
Mathematical Basis of Sensor Fusion in Intrusion Detection Systems.
Sensor Fusion for Position Estimation in Networked Systems.
M2SIR: A Multi Modal Sequential Importance Resampling Algorithm for Particle.
On passive emitter tracking in sensor networks.
Fuzzy-Pattern-Classifier Based Sensor Fusion for Machine Conditioning.
Feature extraction: techniques for landmark based navigation system.
Sensor Data Fusion for Road Obstacle Detection: A Validation Framework.
Biometrics Sensor Fusion.
Fusion of Odometry and Visual Datas To Localization a Mobile Robot.
Probabilistic Mapping by Fusion of Range-Finders Sensors and Odometry.
Sensor fusion for electromagnetic stress measurement and material characterisation.
Iterative Multiscale Fusion and Night Vision Colorization of Multispectral Images.
Super-Resolution Reconstruction by Image Fusion and Application to Surveillance Videos Captured by Small Unmanned Aircraft Systems.
