Abstract
Implementation of a data fusion system is a complex task. Several of the most critical issues related to the implementation are requirements analysis, sensor selection, architecture selection, algorithm selection, software implementation and testing and evaluation. A number of data fusion frameworks have been developed to serve the purpose. This article reviews the literature on data fusion models, as well as aspects of systems engineering related to multisensory fusion. A novel generic framework is proposed to link data fusion system engineering with algorithm engineering paradigm. A new term called ‘impact factor’ is introduced to designate data fusion performance research findings.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.