Salīdzināt metodes

	Sensoru fūzija	Datu fūzija
Nozare	Datu apvienošana	Datu apvienošana
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	2013	1997
Autors	Khaleghi, Khamis, Karray & Razavi	David Hall & James Llinas
Tips	Multi-source information integration pipeline	Multi-level information integration pipeline
Pirmavots	Khaleghi, B., Khamis, A., Karray, F. O., & Razavi, S. N. (2013). Multisensor data fusion: A review of the state-of-the-art. Information Fusion, 14(1), 28–44.	Hall, D. L., & Llinas, J. (1997). An introduction to multisensor data fusion. Proceedings of the IEEE, 85(1), 6–23.
Citi nosaukumi	Multisensor Data Fusion, Multi-Sensor Integration, Information Fusion, Sensör Füzyonu	Sensor Data Fusion, Information Fusion, Multi-source Data Fusion, Veri Füzyonu
Saistītās	3	3
Kopsavilkums	Sensor fusion is a computational process that combines data from multiple heterogeneous sensors to produce an estimate of the environment that is more accurate, complete, and reliable than any single source alone. Systematized as a formal field by Khaleghi, Khamis, Karray, and Razavi in their 2013 state-of-the-art review in Information Fusion, the discipline addresses imperfections such as noise, incompleteness, temporal misalignment, and conflicting readings that arise whenever multiple sensing modalities operate in parallel.	Data fusion is a multi-level process that combines data and information from multiple sensors and sources to achieve improved accuracy, completeness, and confidence in estimates that cannot be obtained from any single source alone. Formally introduced as the Joint Directors of Laboratories (JDL) model by Hall and Llinas in 1997, the framework organizes fusion into hierarchical processing levels ranging from raw signal combination to higher-order situation and threat assessment.