A Multi-Modal Unscented Kalman Filter for Inference of Aircraft Position and Taxi Mode from Surface Surveillance Data
نویسندگان
چکیده
We describe a multi-modal unscented Kalman filter developed for estimation of aircraft position, velocity and heading from noisy surface surveillance data. The raw data is composed of tracks generated by the Airport Surface Detection Equipment, Model-X at Boston Logan International Airport, and is obtained from the Runway Status Lights system. The multi-modal filter formulation facilitates estimation of aircraft taxi mode, described by different acceleration and turn rate values, in addition to aircraft states.
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