Data fusion for situation assessment
Modern systems collect data from many sensors at once. Data fusion combines them into one consistent picture; situation assessment (level 2 of the JDL fusion model) asks what that picture means.
- The JDL data fusion model and how situation assessment breaks down into subproblems.
- Evidence accrual approaches: Bayesian taxonomy and Dempster–Shafer theory, and where probabilistic classifiers fail.
- Kalman filter, fuzzy logic and the fuzzy Kalman filter for estimating states under uncertainty.
Tools
Sensor fusionBayesian inferenceDempster–ShaferKalman filterFuzzy logic
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