Radar and DoA Estimation

In the field of radar and direction-of-arrival (DoA) estimation, the main goal is to detect objects and to estimate their defining parameters, e.g., their position, velocity, and scattering behavior. This information plays a crucial role in a multitude of applications such as autonomous driving, air traffic control, or channel estimation. Whereas active sensing systems, such as radars, transmit a probing signal, passive sensing systems rely on signals from other sources to obtain an estimate of the target object’s parameters.

The main goals are the reduction of computational complexity and the improvement of resolution, flexibility, and adaptivity. For example, coherent MIMO radar and near field measurement scenarios are research fields where high resolution is necessary in order to detect and identify closely spaced objects.

In our research, we focus on novel parameter estimation algorithms, e.g., for the joint estimation of range, angle, velocity, and reflectivity of the targets in the measurement scene. To that end, we apply and develop low-complexity algorithms as well as high-resolution methods using techniques from array signal processing, machine learning and compressed sensing. Our work aims at robust, efficient, and effective algorithms for these sensing systems.