Microwave (MW) fields with strong field strength, ultralow phase-noise, and tunable polarization are crucial for stabilizing and manipulating ultracold polar molecules, which have emerged as a promising platform for quantum science. In this article, we present the design, characterization, and performance of a robust MW setup tailored for precise control of molecular states. This setup achieves a high electric field intensity of 6.9 kV/m in the near-field from a dual-feed waveguide antenna, enabling a Rabi frequency as high as 71 MHz for the rotational transition of sodium-potassium molecules. In addition, the low noise signal source and controlled electronics provide ultralow phase-noise and dynamically tunable polarization. Narrowband filters within the MW circuitry further reduce phase noise by more than 20 dB at 20 MHz offset frequency, ensuring prolonged one-body molecular lifetimes up to 10 s. We also show practical methods to measure the MW field strength and polarization using a simple homemade dipole probe and to characterize phase-noise down to -170 dBc/Hz using a commercial spectrum analyzer and a notch filter. Those capabilities allowed us to evaporatively cool our molecular sample to deep quantum degeneracy. Furthermore, the polarization tunability enabled the observation of field-linked resonances and facilitated the creation of field-linked tetramers. These techniques advance the study of ultracold polar molecules and broaden the potential applications of MW tools in other platforms of quantum science.

This paper introduces a design strategy for integrating a compact radar module with a dielectric gradient-index (GRIN) Luneburg lens, characterized by configurable refractive index variations to enhance the radar’s detection range. This configuration employs computational analysis of dual-beam masks, consisting of two exponentially tapered rods that modify the permittivity distribution of the conventional Luneburg lens, thereby providing superior focusing for both the radar’s transmitter and receiver microstrip array antennas. Compared to conventional radar systems without the lens, the proposed design achieved a 7.75 dB gain enhancement for both TX and RX antennas along the boresight, which significantly exceeds a 2.4-times increase in the radar’s detection range in both the elevation and azimuth directions.

This work presents the application of two movable antennas in a compact radar test range for testing the angular resolution of radar systems in an automotive environment. The goal is to simulate two targets in the azimuth direction, which are measured by a radar placed in the quiet zone. At first, a mathematical approach to the problem is presented. Afterwards, a ray tracer in MATLAB is used for the setup simulation, and measurements are carried out to validate the calculation and simulation results. The effects occurring in the simulation and measurements are analyzed, and strategies to mitigate them are presented. Overall, the results look promising, and the system is suitable for testing the angular resolution of radar systems.

This work presents a ray-tracing simulation approach for an automotive compact radar test range. The goal is to generate two targets separated in azimuthal direction to test the angular resolution of a radar under test. The setup is programmed as a ray-tracer in Matlab, with the application of a wave function to the rays. The effects which occur due to the offset of the antennas from the focus point are analyzed. The system is realized with movable antennas to enable different angular distances.

Road debris is one of the top five causes of serious road traffic accidents in the United States, accounting for about 35,000 crashes every year. For automated driving systems, it is therefore critical to identify and categorize road debris objects reliably. However, only little is known about the behavior and characteristics of road litter in modern automobile radar sensors. An analytical approach for a better understanding of the behavior of road debris in millimeter-wave radar is described on the basis of simple shapes whose RCS characteristics can be calculated. Therefore, a complex-shaped object is divided into essential parts. The RCS of the target is then analyzed concerning the radar frequency and aspect angle. Subsequently, a simulation using a raytracing method for RCS determination validates the analysis of the abstract model. The simulation is then extended to a real object under investigation to further understand of the RCS behavior in the dependency of frequency shifts within the radar signal. Finally, a unique detection method based on the behavior of the RCS characteristics for the researched item is presented for modern vehicle radar systems.

This document proposes the development, manufacturing, and measurement results of a metal 3D printed corrugated conical horn antenna for the E-band (60 to 90 GHz). After a short introduction to the printing technology, the design process of the antenna is presented. The corrugated design is adapted to be compatible to the additive manufacturing (AM) process. After the printing process, the antenna is investigated in terms of dimensional tolerance and surface roughness. The comparison between simulation and measurement yields good results.

In this work, two possibilities for over-the-air synchronization of distributed radar systems are evaluated in simulation. Therefore, a direct path between the radar nodes is used to establish a reference link by which all necessary parameters can be estimated. Additionally, a synchronization with less effort but using a target is compared. Simulations show that both synchronization techniques can achieve a coherent antenna array through signal processing. Additionally, a 3D-printed antenna is proposed to enable a direct path between the radar nodes.

In this paper, a trilateration-based technique for enhancing elevation angle resolution using a 77 GHz FMCW bistatic radar configuration that requires only a few antennas is proposed. The setup involves placing two radar nodes at a considerable spatial distance above each other. The efficacy of the proposed approach is evaluated by simulations using a simple one-ray model, and then by measurements using two radar evaluation boards. The findings indicate that the proposed bistatic system offers superior elevation angle resolution in short-range scenarios compared to traditional monostatic radars, while keeping the setup simple and low in complexity.

A biprism is used to generate two virtual radar targets out of one real target. The concept is introduced and explained. A ray tracer to emulate an FMCW radar system is implemented in Matlab to simulate the test cases. Simple test cases with a radar, a prism, and a shortened horn antenna are performed to verify the concept. In one test case, the radar is centered. In the other test case, the RX antennas are centered relative to the prism. The distance between the radar and the prism was altered between 15cm and 30cm. After receiving promising results, the setup is implemented into a compact range, and the same simulations and measurements are performed. Overall, the angular differences between the targets obtained by the measurements and simulations are a good match to the calculated values. The absolute angles show some deviation. Looking only at the results outside a compact test range, three instead of two targets can appear. The best results are received from the compact test range approach.

In this work, the near-field effects for widely separated coherent FMCW radar networks are analyzed and simulated. With the help of the ambiguity function, a paradigmatic radar network consisting of 4 sensors is investigated for different scenarios. Therefore, different models are derived and simulated. In addition, the influence of the radar parameters is scrutinized. The results show that for long-range scenarios, an adjusted estimator is often necessary, whereas in short-range scenarios, a range compensation with a matched filter is needed. With the help of the described models, it can be assessed which signal processing is necessary for the respective distributed radar system.

In this paper, the feasibility of using additive manufacturing (AM) technologies for the fabrication of corrugated horn antennas for the E-band (60 to 90 GHz) is investigated. Stereolithography apparatus (SLA) and selective laser melting (SLM) are identified as the most suitable technologies for manufacturing horn antennas in this frequency range. To ensure good manufacturing, slanted corrugations are utilized. The antennas have a gain of 13 dBi at 72 GHz and are designed in CST Microwave Studio. For the fabrication of the plastic parts, SLA and the finer-scaled projection micro stereolithography (P mu SL) technology are applied. The metal antennas are printed with direct metal laser sintering (DMLS) from the aluminum alloy AlSi10Mg 10 Mg and the finer scaled micro metal laser sintering (mu MLS) from 316L stainless steel. Overall, four antennas are fabricated. The plastic antennas are plated with copper. Dimensional tolerances and surface roughness of the antennas are evaluated. The antennas are investigated considering H- and E-plane beam shapes, input reflection, and realized gain. The measurement is conducted in an anechoic chamber using the Single-Antenna method. The mu MLS antenna supplies the best results.

This study presents an investigation on the use of anti-reflective (AR) coatings for dielectric corner reflectors (DCR) in radar engineering. DCRs have not been extensively researched for radar applications in the past, but have the potential to enhance the radar cross section (RCS) of objects or for measurement and testing. Our research examines the monostatic RCS behavior of the DCR over a range of different relative permittivities, and presents simulations to validate the concept of AR coatings. The results demonstrate that the use of AR coatings can mitigate interference effects that occur with perpendicular illumination, significantly increase the overall RCS and greatly enhance the opening angle of DCRs. Additionally, the impact on the bistatic RCS is also investigated.

For a reliable detection and classification of road users in modern automotive radar systems, latest research introduces machine-learning (ML) based algorithms in competition to implementations based on the classical radar signal processing chain. Suitable training datasets for ML systems based on real-world radar measurements are however either rarely available or lack the specific radar raw data. A training approach based on transfer-learning methods from data generated by a simulation framework is presented for the range-Doppler-representation of radar measurement data. In particular, the impact of dataset size and sample quality in relation to the performance of the ML system in the radar domain is examined.

This paper presents a quasi-CDMA synchronization technique for a bistatic loosely coupled frequency-modulated continuous wave (FMCW) radar system. The proposed method utilizes a shared low-frequency reference and implements synchronization through subsequent signal processing. The system configuration, signal model, and post-processing steps for phase coherency establishment are discussed. Experimental measurements using FMCW radar modules verify the effectiveness of the proposed technique in achieving phase-synchronized bistatic measurements. The results demonstrate the feasibility of phase synchronization without the need for additional hardware.

In this work, a synthetic aperture radar setup is used for analyzing the mmWave scattering of road surfaces in the automotive 77 GHz band in the laboratory. With this setup, samples of concrete roads in two different surface conditions are investigated, determining the variances in reflectivity depending on material composition and surface structure. Afterward, the distribution of these variations is fitted using probability density functions, namely normal and rayleigh distribution fits. Consequently, the diffuse scattering behavior of concrete roads can be described mathematically. Additionally, previously presented porous asphalt roads are compared and fitted analogously to get a summary of the scattering for all common road surfaces in Germany. Furthermore, a validation of the measurement and the processing by analyzing particularly generated reference samples is performed.

In this paper, the effects of the engine hood on an FMCW radar in an elevated mounting position is evaluated. The setup is analyzed for possible reflections on the engine hood, resulting in a lower and upper limit for the height of targets that can cause a reflection. The findings are then verified by measurements showing the applicability of the bounds. Further, unexpected effects and possible solutions for arising problems are discussed.

Frequency modulated continuous wave radar systems are a vital and widespread component in modern vehicles. Their ability to sense the surrounding environment quickly and reliably is heavily used in today’s driving assistance systems. Latest applied research introduced machine-learning based algorithms for real time detection and classification of radar targets without the need of traditional radar signal processing. The reliable and fast characteristics of these systems are a huge improvement of protecting vulnerable road users like pedestrians and bicyclists, overcoming the traditional methods of radar signal processing. In exchange, machine learning based systems need to be trained with a suitable dataset representing as many as possible real-world case scenarios. Refining adequate datasets from raw sensor data is a time- and cost-consuming effort. In order to achieve the best results, the sensor data must be manually processed and labeled after measuring the use-case in a real-world environment. Hence the application of transfer learning approaches derived from computer-based vision algorithms in automobile radar processing is investigated. A synthetical dataset including labeled radar readings is proposed to eliminate the necessity for manual dataset construction. Transfer learning approaches for machine-learning based radar processing algorithms are explored using a synthetic dataset to enhance detection and classification performance in automotive-related applications. The use of transfer learning already improves the effectiveness of activities based on machine learning for detection and classification in related applications like ship detection with synthetic aperture radar.

Millimeter wave measurements and simulations of dielectric trihedral corner reflectors are presented. Similar to conventional metallic corner reflectors they exhibit retroreflective properties but show interference effects for perpendicular incidence. This leads to significantly fluctuating values of the radar cross section in dependency of the reflector size and material constants. A mathematical proof is given, showing that the path length through a trihedral is constant for perpendicular incidence. This serves as the basis for deriving an analytical model of the radar cross section to evaluate design parameters for dielectric corner reflectors.

Frequency modulated continuous wave radars are an important component of modern driver assistance systems and enable safer automated driving. To achieve real time detection and classification of multiple road users in the range-Doppler map, the usage of neural target detection networks is proposed. Since the amount of labelled radar measurements available limits the training process, a new radar simulation framework is presented which generates arbitrary traffic scenarios with reflection models for pedestrians, bicyclists and vehicles. With an adaptive FMCW setup, sequences of dynamic urban multi-target radar measurements are simulated, maintaining minimum computational complexity. Solely trained on simulated measurement data, the neural network achieves an average precision above 87% on bicyclists and vehicles in real measurement data which is comparable to the performance of neural networks trained on real measurement datasets.

This paper presents the effects of antennas on generated targets when using radar target simulators. A short introduction about radar target generators is given and the reason for ghost targets is discussed. Afterwards, effects of distortion on the generated targets are estimated by means of amplitude and phase change. Different horn antennas were simulated, to examine reflection effects on aperture and mismatch. Furthermore, methods to diminish the impact on the generated targets are simulated and presented. This includes aperture change, attenuation, matching, and polarization changes in the test setup.