Multisensor Fusion


Multisensor Fusion

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 960 p.
  • 言語 ENG
  • 商品コード 9781402007231
  • DDC分類 600


Examines the underlying principles of sensor operation and data fusion, the techniques and technologies that enable the process, including the operation of 'fusion engines'.

Full Description

For some time, all branches of the military have used a wide range of sensors to provide data for many purposes, including surveillance, reconnoitring, target detection and battle damage assessment. Many nations have also attempted to utilise these sensors for civilian applications, such as crop monitoring, agricultural disease tracking, environmental diagnostics, cartography, ocean temperature profiling, urban planning, and the characterisation of the Ozone Hole above Antarctica. The recent convergence of several important technologies has made possible new, advanced, high performance, sensor based applications relying on the near-simultaneous fusion of data from an ensemble of different types of sensors. The book examines the underlying principles of sensor operation and data fusion, the techniques and technologies that enable the process, including the operation of 'fusion engines'. Fundamental theory and the enabling technologies of data fusion are presented in a systematic and accessible manner. Applications are discussed in the areas of medicine, meteorology, BDA and targeting, transportation, cartography, the environment, agriculture, and manufacturing and process control.


Preface. 1: Introduction and Fundamentals. Information Fusion in the Human Brain; R. von Hanwehr. Fundamentals of Reasoning and Multisensing; E. Waltz. Introduction to DF: Models and Processes, Architectures, Techniques and Applications; E. Shahbazian. The Fusion of Decisions for Distributed Recognition; M.D. Bedworth. Reexamining Data Fusion Processing at Levels 2, 3, and 4; J. Llinas. 2: Multisensor Fusion Theory. An Introduction to Distributed Detection Theory; P.K. Varshney. Distributed Sensor Networks and Neural Trees for Multisensor Data Fusion in Computer Vision; G.L. Foresti. Architectures for Efficient Data Fusion; P. Vangasse, D. Nicholson. Reasoning Frameworks; P. Valin. Random Sets and Unification; P. Valin. Fusion of Information under Imprecision and Uncertainty, Numerical Methods, and Image Information Fusion; I. Bloch. Multisensor Fusion under Unknown Distributions Finite-Sample Performance Guarantees; N.S.V. Rao. Data Association and Multitarget Tracking; J.-P. Le Cadre. Wavelets for Modeling and Data Fusion in Remote Sensing; T. Ranchin. Soft Sensor Management for Multisensor Tracking Algorithm; V. Nimier. Intellectualization of Multi-Sensor System for Decision Making Process; T.E. Bekmuratov. 3: Multisensor Design and Implementation. Implementing Data Fusion Systems; R. Reynaud. The Implementation of Data Fusion Systems; D.L. Hall. Multisensor Data Fusion Using Kalman Filters Based on Neuro-Fuzzy Linearisation; C. Harris, Q. Gan. Identify Information Fusion through Evidential Reasoning; É. Bossé. Association Techniques Used in Multisensor Data Fusion; E. Semerdjiev. Change Detection through Multisensor Processing; E. Semerdjiev.Statistical, Logic Based, and Neural Network Based Methods for Mining Rules from Data; M. Holena. Multi-Aspect Data Fusion Applied to Electromagnetic Target Classification Using Enetic Algorithm; G. Turhna-Sayan. Object Detection and Tracking in Distributed Surveillance Systems Using Multiple Cameras; C.S. Regazzoni, L. Marcenaro. An Adaptive Filter for Tracking Targets in Clutter; M. Efe. Tracking Closely Maneuvering Targets in Clutter with an IMM-JVC Algorithm; A. Jouan, et al. Robust Multisensor Image Registration with Partial Distance Merits; Y. Sheng, et al. Detection, Characterization and Classification of Radio Transmitter Turn-on Transients; O. Ürenten, N. Serinken. Optimization and Benchmarking of Truncated Dempster-Shafer for Airborne Surveillance; P. Valin, D. Boily. Multitarget Tracking in Electronically Scanned Antenna Radar; A. Witczak, M. Brzozowski. 4: Multisensor Fusion Applications. Data Fusion in Remote Sensing and Improvement of the Spatial Resolution of Satellite Images; T. Ranchin. Introduction to Data Fusion and Applications in Astrodynamics; D. Finkleman, et al. Landmine Problem and Multisensor Detection; V.M. Bystritskii. Multisensing in Road Traffic Measurements; R. Sroka. Information Fusion Applied to Selected Financial Problem Domains; D. Lowe. Computer Network Security; E. Lefebvre. Multisensing in Chernobyl: The State and Monitoring of Object 'Shelter'; I.N. Onishchenko. Blackboard Architectures for Sonar Data Association; B.A. McArthur. On the Use of Statistical Considerations in Multi-Modal Identity Verification System Design; P. Verlinde, M. Acheroy. Multisensory Experiments on the Meson Facilities; V.M. Bystritskii. Development of Remote Sensing Technology for Detection of Nuclear Explosiv