Florian Meyer's research is focused on statistical signal processing for navigation, mapping, and multiobject tracking in applications including maritime situational awareness, autonomous driving, and indoor localization. His work investigates efficient and scalable high-dimensional nonlinear estimation using graphical models where the number of states to be estimated may also be unknown. He develops signal processing methods which enable the consistent combination of information provided by a large number of spatially separated heterogeneous sensors and exploit physical effects such as multiple propagation paths. Techniques resulting from his research have been evaluated using different robotic platforms as well as a variety of sensing technologies such as ultra-wideband radios, high frequency surface wave radars, passive sonar arrays, and multistatic sonar networks.