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A novel design methodology is presented to mitigate scan blindness in cavity antenna arrays without the need for any changes on the radiating structure itself. For a first proof-of-concept demonstration, a fully PCB-compliant dual-polarized cavity element is loaded by vertical stubs to manipulate the dispersion characteristics in the aperture plane. In contrast with its conventional cavity antenna counterpart, the proposed stub-loaded unit cell element shows through scattering and eigenmode analysis that the vertical stubs may effectively enhance the antenna’s wide-angle scan performance by preventing the onset of surface and leaky wave resonances. Owing to this additional design freedom, an element gain improvement of at least 1 dB is achieved, due to a truly TE and TM mode-free characteristic along the lateral directions. A dual-polarized 11 $\times$ 11 array prototype was implemented. The measurement results are in very good agreement with those obtained by full-wave simulations. The realized stub-loaded cavity element exhibits reflection coefficients lower than −10 dB with a very low inter-port coupling $\vartheta$ )-pattern for 60° E- and H-plane scans from 28 GHz to 31.5 GHz without oversampling the aperture.

Although the beginning of research on automotive radar sensors goes back to the 1960s, automotive radar has remained one of the main drivers of innovation in millimeter wave technology over the past two decades. Today, millions of sensors are produced each year, which was made possible by inexpensive and mature millimeter wave technology. The technology maturity, in turn, enables research to be carried out on systems that are considerably more complex and powerful than was possible just a few years ago. The focus of research has thus shifted from purely hardware-oriented and device-level topics to sophisticated millimeter wave systems and RF signal processing topics. This opens up new research topics such as digital modulation schemes, radar networks, radar imaging, and machine learning. In this review paper, we sketch the path from the very beginning through the state of the art with sophisticated multiple-input multiple-output (MIMO) antenna arrays and mature assembly and interconnect concepts to today's key research topics of automotive radar.

Crossmodal interaction in situated language comprehension is important for effective and efficient communication. The relationship between linguistic and visual stimuli provides mutual benefit: While vision contributes, for instance, information to improve language understanding, language in turn plays a role in driving the focus of attention in the visual environment. However, language and vision are two different representational modalities, which accommodate different aspects and granularities of conceptualizations. To integrate them into a single, coherent system solution is still a challenge, which could profit from inspiration by human crossmodal processing. Based on fundamental psycholinguistic insights into the nature of situated language comprehension, we derive a set of performance characteristics facilitating the robustness of language understanding, such as crossmodal reference resolution, attention guidance, or predictive processing. Artificial systems for language comprehension should meet these characteristics in order to be able to perform in a natural and smooth manner. We discuss how empirical findings on the crossmodal support of language comprehension in humans can be applied in computational solutions for situated language comprehension and how they can help to mitigate the shortcomings of current approaches.

To fulfill the dual-frequency requirements, elements are needed to resonate at two different, independently adjustably frequencies. A low weight, low cost, and easy to fabricate single-layer dual-frequency reflectarray is designed, fabricated, and measured, with gain values of 27 and 29.2 dBi at 20 and 30 GHz, respectively.