Konferenzbeiträge

Automotive millimeter-wave radar systems are key to automated and connected driving technologies. It is necessary to validate their functional performance in the installed state thoroughly, reliably, and efficiently under realistic conditions before deploying them in real-world traffic. Field-operational tests are the ultimate phase of verification and validation of radar sensors. This approach offers the highest degree of realism yet consuming enormous resources and associated risks. Additionally, these drive tests are neither sufficiently reproducible nor controllable. On the other hand, computer simulation-based closed-loop test approaches overcome these limitations, but lack physically realistic environments. Therefore, over-the-air testing approaches have gained great relevance in this context. In earlier work, we proposed an advanced system concept using an over-the-air vehicle-in-the-loop (OTA/ViL) approach for evaluating the installed performance of fully operational automotive radar systems. In this paper, we present the complete test system in a closed loop in a virtual electromagnetic environment with realistic radar target echoes. An exemplary traffic scenario is considered to validate the performance of the implemented test system. Initial measurements provide promising results.

A studied magnetic field sensor is based on resonant operation of magnetoelectric micro-electro-mechanical systems (MEMS). Subsequently to an applied magnetic field, the micro beam changes the eigenfrequency, due to the magnetostrictive effect. Euler-Bernoulli beam theory can calculate eigenfrequencies of bending vibrations of beams with high accuracy. Implementing more complex beam geometries is challenging, thus often the finite element method (FEM) is used. This paper deals with the modeling of prestressed beams with multilayered structure and discontinuities along the beam length using Euler-Bernoulli beam theory. The arising problems are addressed in detail. As an example, the model is applied to the studied magnetoelectric sensor and shows good accordance to FEM simulations. An optimization algorithm is used to find a sensor geometry that leads to high output signals utilizing the developed model as input for the minimization of a target function.

We present a novel and low-complexity massive multiple-input multiple-output (MIMO) precoding strategy based on novel findings concerning the subspace separability of Rician fading channels. Considering a uniform rectangular array at the base station, we show that the subspaces spanned by the channel vectors can be factorized as a tensor product between two lower dimensional subspaces. Based on this result, we formulate tensor maximum ratio transmit and zero-forcing precoders. We show that the proposed tensor precoders exhibit lower computational complexity and require less instantaneous channel state information than their linear counterparts. Finally, we present computer simulations that demonstrate the applicability of the proposed tensor precoders in practical communication scenarios.

A framework is proposed for developing and evaluating algorithms for extracting multipath propagation components (MPCs) from measurements collected by sounders at millimeter-wave (mmW) frequencies. To focus on algorithmic performance, an idealized model is proposed for the spatial frequency response of the propagation environment measured by a sounder. The input to the sounder model is a pre-determined set of MPC parameters that serve as the "ground truth". A three-dimensional angle-delay (beamspace) representation of the measured spatial frequency response serves as a natural domain for implementing and analyzing MPC extraction algorithms. Metrics for quantifying the error in estimated MPC parameters are introduced. Initial results are presented for a greedy matching pursuit algorithm that performs a least-squares (LS) reconstruction of the MPC path gains within the iterations. The results indicate that the simple greedy-LS algorithm has the ability to extract MPCs over a large dynamic range, and suggest several avenues for further performance improvement through extensions of the greedy-LS algorithm as well as by incorporating features of other algorithms, such as SAGE and RIMAX.