Application of Multi-Sensor Fusion Technology in Target Detection and Recognition

Application of Multi-Sensor Fusion Technology in Target Detection and Recognition
Author: Jukka Heikkonen
Publisher: Mdpi AG
Total Pages: 168
Release: 2022-03-04
Genre: Mathematics
ISBN: 9783036513522

Download Application of Multi-Sensor Fusion Technology in Target Detection and Recognition Book in PDF, Epub and Kindle

Application of multi-sensor fusion technology has drawn a lot of industrial and academic interest in recent years. The multi-sensor fusion methods are widely used in many applications, such as autonomous systems, remote sensing, video surveillance, and the military. These methods can obtain the complementary properties of targets by considering multiple sensors. On the other hand, they can achieve a detailed environment description and accurate detection of interest targets based on the information from different sensors. This book collects novel developments in the field of multi-sensor, multi-source, and multi-process information fusion. Articles are expected to emphasize one or more of the three facets: architectures, algorithms, and applications. Published papers dealing with fundamental theoretical analyses, as well as those demonstrating their application to real-world problems.

A New Multi-Sensor Fusion Target Recognition Method Based on Complementarity Analysis and Neutrosophic Set

A New Multi-Sensor Fusion Target Recognition Method Based on Complementarity Analysis and Neutrosophic Set
Author: Yuming Gong
Publisher: Infinite Study
Total Pages: 18
Release:
Genre: Mathematics
ISBN:

Download A New Multi-Sensor Fusion Target Recognition Method Based on Complementarity Analysis and Neutrosophic Set Book in PDF, Epub and Kindle

To improve the efficiency, accuracy, and intelligence of target detection and recognition, multi-sensor information fusion technology has broad application prospects in many aspects. Compared with single sensor, multi-sensor data contains more target information and effective fusion of multi-source information can improve the accuracy of target recognition. However, the recognition capabilities of different sensors are different during target recognition, and the complementarity between sensors needs to be analyzed during information fusion. This paper proposes a multi-sensor fusion recognition method based on complementarity analysis and neutrosophic set. The proposed method mainly has two parts: complementarity analysis and data fusion. Complementarity analysis applies the trained multi-sensor to extract the features of the verification set into the sensor, and obtain the recognition result of the verification set. Based on recognition result, the multi-sensor complementarity vector is obtained. Then the sensor output the recognition probability and the complementarity vector are used to generate multiple neutrosophic sets. Next, the generated neutrosophic sets are merged within the group through the simplified neutrosophic weighted average (SNWA) operator. Finally, the neutrosophic set is converted into crisp number, and the maximum value is the recognition result. The practicality and effectiveness of the proposed method in this paper are demonstrated through examples.

Multi-Sensor Information Fusion

Multi-Sensor Information Fusion
Author: Xue-Bo Jin
Publisher: MDPI
Total Pages: 602
Release: 2020-03-23
Genre: Technology & Engineering
ISBN: 3039283022

Download Multi-Sensor Information Fusion Book in PDF, Epub and Kindle

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.

Multisensor Fusion

Multisensor Fusion
Author: Anthony K. Hyder
Publisher: Springer Science & Business Media
Total Pages: 929
Release: 2012-12-06
Genre: Computers
ISBN: 9401005567

Download Multisensor Fusion Book in PDF, Epub and Kindle

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.

Advances and Challenges in Multisensor Data and Information Processing

Advances and Challenges in Multisensor Data and Information Processing
Author: E. Lefebvre
Publisher: IOS Press
Total Pages: 412
Release: 2007-05-11
Genre: Business & Economics
ISBN: 1607502321

Download Advances and Challenges in Multisensor Data and Information Processing Book in PDF, Epub and Kindle

Information fusion resulting from multi-source processing, often called multisensor data fusion when sensors are the main sources of information, is a relatively young (less than 20 years) technology domain. It provides techniques and methods for: Integrating data from multiple sources and using the complementarity of this data to derive maximum information about the phenomenon being observed; Analyzing and deriving the meaning of these observations; Selecting the best course of action; and Controlling the actions. Various sensors have been designed to detect some specific phenomena, but not others. Data fusion applications can combine synergically information from many sensors, including data provided by satellites and contextual and encyclopedic knowledge, to provide enhanced ability to detect and recognize anomalies in the environment, compared with conventional means. Data fusion is an integral part of multisensor processing, but it can also be applied to fuse non-sensor information (geopolitical, intelligence, etc.) to provide decision support for a timely and effective situation and threat assessment. One special field of application for data fusion is satellite imagery, which can provide extensive information over a wide area of the electromagnetic spectrum using several types of sensors (Visible, Infra-Red (IR), Thermal IR, Radar, Synthetic Aperture Radar (SAR), Polarimetric SAR (PolSAR), Hyperspectral...). Satellite imagery provides the coverage rate needed to identify and monitor human activities from agricultural practices (land use, crop types identification...) to defence-related surveillance (land/sea target detection and classification). By acquiring remotely sensed imagery over earth regions that land sensors cannot access, valuable information can be gathered for the defence against terrorism. This books deals with the following research areas: Target recognition/classification and tracking; Sensor systems; Image processing; Remote sensing and remote control; Belief functions theory; and Situation assessment.

Multisensor Data Fusion

Multisensor Data Fusion
Author: David Hall
Publisher: CRC Press
Total Pages: 564
Release: 2001-06-20
Genre: Technology & Engineering
ISBN: 1420038540

Download Multisensor Data Fusion Book in PDF, Epub and Kindle

The emerging technology of multisensor data fusion has a wide range of applications, both in Department of Defense (DoD) areas and in the civilian arena. The techniques of multisensor data fusion draw from an equally broad range of disciplines, including artificial intelligence, pattern recognition, and statistical estimation. With the rapid evolut