Sensor and Data Fusion

Sensor and Data Fusion

The methods provided by sensor and data fusion are important tools for fusing large sets of mutually complementary data end efficiently exploiting the sensor systems available.

Description

A challenging exploitation technology at the common interface between sensors, command & control systems, and the human decision makers involved, this technology plays a key role in applications with time-critical situations or in situations with a high decision risk, where human deficiencies are to be compensated by automatically or interactively working fusion techniques.

Table of Contents

  • Advanced Sensor and Dynamics Models with an Application to Sensor Management
  • Target Data Association Using a Fuzzy-Logic Based Approach
  • Data Fusion Performance Evaluation for Dissimilar Sensors: Application to Road Obstacle Tracking
  • IR Barrier Data Integration for Obstacle Detection
  • A Model of Federated Evidence Fusion for Real-Time Traffic State Estimation
  • Multi Sensor Data Fusion Architectures for Air Traffic Control Applications
  • Sensor Data Fusion in Automotive Applications
  • Multisensor Data Fusion Strategies for Advanced Driver Assistance Systems
  • Trajectory Generation and Object Tracking of Mobile Robot Using Multiple Image Fusion
  • Multisensory Data Fusion for Ubiquitous Robotics Services
  • Design of an Intelligent Housing System Using Sensor Data Fusion Approaches
  • Model-based Data Fusion in Industrial Process Instrumentation
  • Multi-Sensor Data Fusion in Presence of Uncertainty and Inconsistency in Data
  • Updating Scarce High Resolution Images with Time Series of Coarser Images: a Bayesian Data Fusion Solution
  • Multi-Sensor & Temporal Data Fusion for Cloud-Free Vegetation Index Composites
  • Three Strategies for Fusion of Land Cover Classification Results of Polarimetric SAR Data
  • Multilevel Information Fusion: A Mixed Fuzzy Logic/Geometrical Approach with Applications in Brain Image Processing
  • Anomaly Detection & Behavior Prediction: Higher-Level Fusion Based on Computational Neuroscientific Principles
  • A Biologically Based Framework for Distributed Sensory Fusion and Data Processing
  • Agent Based Sensor and Data Fusion in Forest Fire Observer
  • A Sensor Data Fusion Procedure for Environmental Monitoring Applications by a Configurable Network of Smart Web-Sensors
  • Monitoring Changes in Operational Scenarios via Data Fusion in Sensor Networks
  • Elements of Sequential Detection with Applications to Sensor Networks
  • Parameter Estimation Over Noisy Communication Channels in Distributed Sensor Networks
  • Monte Carlo Methods for Node Self-Localization and Nonlinear Target Tracking in Wireless Sensor Networks

Book Details

Author(s): Nada Milisavljevic
Publisher: InTech
Format(s): PDF, HTML
File size: 62.50 MB
Number of pages: 436
Link: Download or read online.








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