Probabilistic Labeling in Radar Track-before-Detect Processing: Algorithms for tracking closely-spaced and/or interacting targets

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 ...

Approximately Optimal Resource Management for Multi-Function Radar: Algorithmic Solutions Using a Generic Framework

Recent advances in Multi-Function Radar (MFR) systems led to an increase in their degrees of freedom. As a result, modern MFR systems are capable of adjusting many parameters during runtime. An automatic adaptation of the radar system to changing situations, like weather conditions, interference, or target maneuvers, is often mentioned in the...