Multi-Sensor Information Fusion

• Main Author: Gao, Yuan (auth)
• Other Authors: Jin, Xue-Bo (auth)
• Format: Electronic Book Chapter
• Language: English
• Published: MDPI - Multidisciplinary Digital Publishing Institute 2020
• Subjects: History of engineering & technology; similarity measure; information filter; out-of-sequence; Hellinger distance; coefficient of determination maximization strategy; uncertainty measure; embedded systems; Internet of things (IoT); random delays; adaptive distance function; random finite set; Dempster-Shafer evidence theory (DST); safe trajectory; health reliability degree; dynamic optimization; state probability approximation; sensors bias; multi-environments; belief entropy; quaternion; closed world; Gaussian process regression; Gaussian mixture model (GMM); intelligent transport system; multirotor UAV; multi-sensor system; attitude; time-domain data fusion; precision landing; Industry 4.0; magnetic angular rate and gravity (MARG) sensor; uncertainty; unscented information filter; data classification; high-definition map; global information; inconsistent data; extended belief entropy; sensor system; Steffensen's iterative method; SLAM; the Range-Range-Range frame; evidential reasoning; belief functions; powered two wheels (PTW); electronic nose; particle swarm optimization; grey group decision-making; user experience platform; complex surface measurement; DoS attack; extended Kalman filter; ICP; Gaussian density peak clustering; artificial marker; random parameter matrices; optimal estimate; local structure descriptor; object classification; domain adaption; networked systems; expectation maximization (EM) algorithm; attitude estimation; Gaussian process model; least-squares smoothing; target positioning; RFS; spectral clustering; maintenance decision; multi-target tracking; GMPHD; time-distributed ConvLSTM model; non-rigid feature matching; unknown inputs; cardiac PET; subspace alignment; gradient domain; multi-sensor measurement; data fusion; Bar-Shalom Campo; Kalman filter; signal feature extraction methods; sensor data fusion algorithm; distributed architecture; predictive modeling techniques; Gaussian mixture model; self-reporting; deep learning; mutual support degree; security zones; sensor array; soft sensor; aircraft pilot; projection; vehicle-to-everything; distributed intelligence system; square-root cubature Kalman filter; information fusion; evidence combination; LiDAR; feature representations; multi-sensor information fusion; linear constraints; galvanic skin response; decision-level sensor fusion; most suitable parameter form; Pignistic vector angle; SINS/DVL integrated navigation; fault diagnosis; facial expression; yaw estimation; dual gating; multi-sensor data fusion; multisensor system; A* search algorithm; data fusion architectures; drift compensation; augmented state Kalman filtering (ASKF); manifold; nested iterative method; data preprocessing; interference suppression; conflicting evidence; sonar network; Gaussian process; health management decision; state estimation; eye-tracking; high-dimensional fusion data (HFD); MEMS accelerometer and gyroscope; multitarget tracking; gaussian mixture probability hypothesis density; integer programming; image registration; Dempster-Shafer evidence theory; linear regression; data association; nonlinear system; covariance matrix; multi-source data fusion; fuzzy neural network; least-squares filtering; fire source localization; network flow theory; weight maps; camera; plane matching; calibration; unmanned aerial vehicle; fixed-point filter; workload; intelligent and connected vehicles; mimicry security switch strategy; alumina concentration; the Range-Point-Range frame; spatiotemporal feature learning; distributed fusion; user experience evaluation; image fusion; vehicular localization; sensor fusion; vibration; parameter learning; weighted fusion estimation; data registration; pose estimation; surface quality control; trajectory reconstruction; land vehicle; square root; Deng entropy; multi-focus; EEG; low-cost sensors; sensor fusing; sensor data fusion; packet dropouts; estimation; industrial cyber-physical system (ICPS); multi-sensor time series; multi-sensor network; Human Activity Recognition (HAR); transfer; multisensor data fusion; convergence condition; interaction tracker; acoustic emission; Covariance Projection method; mix-method approach; orthogonal redundant inertial measurement units; sematic segmentation; Surface measurement; conflict measurement; user experience measurement; observable degree analysis; open world; novel belief entropy; cutting forces; machine health monitoring; Bayesian reasoning method; orientation; surface modelling; hybrid adaptive filtering; supervoxel; RTS smoother; fast guided filter.; multi-sensor joint calibration; principal component analysis
• Online Access: DOAB: download the publication; DOAB: description of the publication

Summary

This book includes papers from the section "Multisensor Information Fusion", from Sensors between 2018 to 2019. It focuses on the latest research results of current multi-sensor fusion technologies and represents the latest research trends, including traditional information fusion technologies, estimation and filtering, and the latest research, artificial intelligence involving deep learning.

Physical Description

1 electronic resource (602 p.)

ISBN

books978-3-03928-303-3
9783039283033
9783039283026

Access

Open Access