Probabilistic Labeling in Radar Track-before-Detect Processing
Algorithms for tracking closely-spaced and/or interacting targets
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Abstract
Radar-tracking of low-observable targets such as drones suffers from low detection performance. In these type of applications, it is desirable to avoid data thresholding in order to preserve the weak target signal in the raw sensor data. This thesis considers the Multiple Object Tracking (MOT) problem in the context of radar Track-before-Detect (TrBD) processing, where the raw radar data is fed into the filtering process without previous compression into a finite set of detection/plots....