Kongress- und Tagungsbeiträge des Fachgebiets Elektronische Messtechnik und SignalverarbeitungKongress- und Tagungsbeiträge des Fachgebiets Elektronische Messtechnik und Signalverarbeitung

Kongress- und Tagungsbeiträge

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Smeenk, Carsten; Schneider, Christian; Thomä, Reiner
Framework for simulation models and algorithms in ISAC networks. - In: 2023 IEEE 3rd International Symposium on Joint Communications & Sensing (JC & S), (2023), insges. 6 S.

In Integrated Sensing and Communications (ISAC), radar and communications functionalities share the same radio channel and radio resources. This sharing allows the deployment of both functionalities at a low cost without additional frequency bands and infrastructure. Because radar and communications have different radio resource requirements, new radio access and radio resource management (RRM) methods are required in a shared system. To develop and evaluate new ISAC methods, this paper presents a modular simulation framework for the system level and link level of ISAC networks. The main components of the framework are the data storage, the simulators, and the algorithms. This paper presents the framework's architecture, the integrated simulation models for channel and signal simulation, and the integrated algorithms for multiple radar target localization and data transmission.



https://doi.org/10.1109/JCS57290.2023.10107507
Wegner, Tim Erich; Gebhardt, Stefan; Del Galdo, Giovanni
Fill level measurements using an M-sequence UWB radar. - In: International journal of microwave and wireless technologies, ISSN 1759-0795, Bd. 15 (2023), 1, S. 74-81

Due to increasingly complex and automated manufacturing processes, the demands on the control parameters of these processes are also increasing. In many applications, such a parameter is the fill quantity, whose precise determination is of ever growing importance. This paper shows with which accuracy and precision an M-sequence ultra-wideband radar can determine levels in small metallic and non-metallic containers with contact-based and contactless measurements. First, the principle of level measurement using guided wave radar is explained and the measurement setup is described. Afterward, the measurement results are shown and discussed. The measurements show that the level can be measured with an accuracy of better than 0.5 mm. In addition, level fluctuations can be detected with a precision of 3 μm. Based on the results of the guided wave radar, the possibilities of volumetric contactless measurement using an electrically small patch antenna are discussed. A particular challenge in contactless level measurement is the high number of multipath components, which strongly influence the accuracy. In addition, there are near-field effects when measuring close to the antenna. Exploiting these near-field effects, an additional method to accurately determine the full state of the container is investigated.



https://doi.org/10.1017/S1759078722000502
Ahmed, Shayan; Gedschold, Jonas; Wegner, Tim Erich; Sode, Adrian; Trabert, Johannes; Del Galdo, Giovanni
Labeling custom indoor point clouds through 2D semantic image segmentation. - In: 2022 Sixth IEEE International Conference on Robotic Computing, (2022), S. 261-264

For effective Computer Vision (CV) applications, one of the difficult challenges service robots have to face concerns with complete scene understanding. Therefore, various strategies are employed for point-level segregation of the 3D scene, such as semantic segmentation. Currently Deep Learning (DL) based algorithms are popular in this domain. However, they require precisely labeled ground truth data. Generating this data is a lengthy and expensive procedure, resulting in a limited variety of available data. On the contrary, the 2D image domain offers labeled data in abundance. Therefore, this study explores how we can achieve accurate labels for the 3D domain by utilizing semantic segmentation on 2D images and projecting the estimated labels to the 3D space via the depth channel. The labeled data may then be used for vision related tasks such as robot navigation or localization.



https://doi.org/10.1109/IRC55401.2022.00050
Vintimilla, Renato Zea; Lorenz, Mario; Landmann, Markus; Del Galdo, Giovanni
Emulation of electromagnetic plane waves for 3D antenna pattern estimation. - In: 2022 IEEE 96th Vehicular Technology Conference:(VTC 2022-Fall), (2022), insges. 6 S.

With the fast development of wireless devices, over-the-air (OTA) testing is becoming the preferred method among developers and manufacturers of wireless equipment. The ability to recreate a scenario under controllable and repeatable conditions keeps the method under constant development, providing new features that increase the realism during the tests. A recent proof of that is the integration of 3D wave field synthesis (3DWFS) to OTA testing, which becomes a significant step to accurately emulate wireless scenarios within a controlled environment.In this context, this contribution improves the OTA system calibration for 3DWFS; efficiently increasing the emulation quality of electromagnetic plane waves impinging from any angular position within an anechoic chamber. In fact, this enhancement implicitly delivers a new method for accurate estimation of the antenna radiation pattern in 3D. This is not only a highly demanded application among antenna manufacturers but in this case also proves the validity of the results and consolidates the integration of 3DWFS to OTA testing.



https://doi.org/10.1109/VTC2022-Fall57202.2022.10013008
Meyer, Lukas; Gedschold, Jonas; Wegner, Tim Erich; Del Galdo, Giovanni; Kalisz, Adam
Enhancement of vision-based 3D reconstruction systems using radar for smart farming. - In: 2022 IEEE International Workshop on Metrology for Agriculture and Forestry, (2022), S. 155-159

Digital field recordings are central to most precision agriculture systems since they can replicate the physical environment and thus monitor the state of an entire field or individual plants. Using different sensors, such as cameras and radar, data can be collected from various domains. Through the combination of radio wave propagation and visible light phenomena, it is possible to enhance, e.g., the optical condition of a fruit with internal parameters such as the water content. This paper proposes a method to correct sensor errors to perform data fusion. As an example, we observe a watermelon with camera and radar sensors and present a system architecture for the visualization of both sensors. For this purpose, we constructed a handheld platform on which both sensors are mounted. In our report, the radar is analyzed in terms of systematic and stochastic errors to formulate an angle-dependent mapping function for error correction. It is successfully shown that camera and radar data are correctly assigned with a watermelon used as a target object, demonstrated by a 3D reconstruction. The proposed system shows promising results for sensor overlay, but radar data remain challenging to interpret.



https://doi.org/10.1109/MetroAgriFor55389.2022.9964699
Kodera, Sayako; Römer, Florian; Pérez, Eduardo; Kirchhof, Jan; Krieg, Fabian
Deep learning aided interpolation of spatio-temporal nonstationary data. - In: 30th European Signal Processing Conference (EUSIPCO 2022), (2022), S. 2221-2225

Despite the growing interest in many fields, spatio-temporal (ST) interpolation remains challenging. Given ST nonstationary data distributed sparsely and irregularly over space, our objective is to obtain an equidistant representation of the region of interest (ROI). For this reason, an equidistant grid is defined within the ROI, where the available time series data are arranged, and the time series of the unobserved points are interpolated. Aiming to maintain the interpretability of the whole process while offering flexibility and fast execution, this work presents a ST interpolation frame-work which combines a statistical technique with deep learning. Our framework is generic and not confined to a specific application, which also provides the prediction confidence. To evaluate its validity, this framework is applied to ultrasound nondestructive testing (UT) data as an example. After the training with synthetic UT data sets, our framework is shown to yield accurate predictions when applied to measured UT data.



https://ieeexplore.ieee.org/document/9909600
Schieler, Steffen; Döbereiner, Michael; Semper, Sebastian; Landmann, Markus
Estimating multi-modal dense multipath components using auto-encoders. - In: 30th European Signal Processing Conference (EUSIPCO 2022), (2022), S. 1716-1720

We present a maximum-likelihood estimation algorithm for radio channel measurements exhibiting a mixture of independent Dense Multipath Components. The novelty of our approach is in the algorithms initialization using a deep learning architecture. Currently, available approaches can only deal with scenarios where a single mode is present. However, in measurements, two or more modes are often observed. This much more challenging multi-modal setting bears two important questions: How many modes are there, and how can we estimate those? To this end, we propose a Neural Net-architecture that can reliably estimate the number of modes present in the data and also provide an initial assessment of their shape. These predictions are used to initialize for gradient- and model-based optimization algorithm to further refine the estimates. We demonstrate numerically how the presented architecture performs on measurement data and analytically study its influence on the estimation of specular paths in a setting where the single-modal approach fails.



https://ieeexplore.ieee.org/document/9909796
Gedschold, Jonas; Wegner, Tim Erich; Kalisz, Adam; Thomä, Reiner; Thielecke, Jörn; Del Galdo, Giovanni
Time-domain analysis of ultra-wideband scattering properties of fruits. - In: 2022 19th European Radar Conference, (2022), S. 77-80

In the present paper we evaluate scattering properties of fruits measured with a short-range Ultra-Wideband radar. This is part of our investigation how effectively such a radar can be used to infer information such as fruit biomass or ripeness in an agricultural environment. The covered frequency band spans from 1.4 to 5.6 GHz. We analyze measured impulse responses of a watermelon, a grapefruit, and an apple with respect to a dependency on the distance between radar and fruit and the observation angle i.e., rotation of the fruit. Measurements are performed under laboratory conditions, however, we analyze the data considering a pre-harvest analysis on a field. It becomes apparent that an analysis of the dispersed dominant reflection of the peel is most promising. Due to the natural growth and hence anisotropy of the fruits, we conclude to average over multiple monostatic observation angles to reduce the natural variations of e.g. the scattered power.



https://doi.org/10.23919/EuRAD54643.2022.9924720
Stanko, Daniel; Sommerkorn, Gerd; Ihlow, Alexander; Del Galdo, Giovanni
Enable SDRs for real-time MIMO channel sounding featuring parallel coherent Rx channels. - In: 2022 IEEE 95th Vehicular Technology Conference:(VTC2022-Spring), (2022), insges. 5 S.

A parallel receiver architecture for multiple input multiple output (MIMO) channel sounding application is presented with a software-defined radio (SDR)-based field-programmable gate array (FPGA) implementation. The receiver covers phase coherent reception via shared local oscillator (LO) and reference clock, a timing scheme synchronous to the antenna switching at the transmitter, and an integrated automatic gain control (AGC) in all receive channels. It is built with SDRs (NI USRP-2955, X310 series with TwinRx daughterboards). The use of these off-the-shelf hardware components reduces the costs of the sounding system. The FPGA implementation together with the system parameters of the chosen hardware allows a minimum AGC update interval of approx. 44.38 μs. Our setup demonstrates the applicability of state-of-the-art SDRs as a sounding system for continuous acquisition of the time variant, space, and frequency selective radio propagation channel.



https://doi.org/10.1109/VTC2022-Spring54318.2022.9860841
Niu, Han; Dupleich, Diego; Völker-Schöneberg, Yanneck; Ebert, Alexander; Müller, Robert; Eichinger, Joseph; Artemenko, Alexander; Del Galdo, Giovanni; Thomä, Reiner
From 3D point cloud data to ray-tracing multi-band simulations in industrial scenario. - In: 2022 IEEE 95th Vehicular Technology Conference:(VTC2022-Spring), (2022), insges. 5 S.

In this paper, we present the ray tracing (RT) simulation in the 3D model of one highly dense clutter industrial hall, which is scanned by laser scanner and reconstructed based on accurate point cloud. The whole processing chain from the scanning of the physical environment to running the simulation is presented in detail. To validate the simulation results, the synthetic channel characteristics and large-scale parameters, including delay spread (DS), angular spread (AS) and path loss (PL), are compared with those obtained from channel sounding measurement in both LOS and NLOS cases, at 6.75 GHz, 30 GHz and 60 GHz. The simulation results show that some scatters are significant in all bands and may be well identified and tracked. This indicates that our target to generate a deterministic channel model or a hybrid channel model at multi-band for industrial scenario may be possible.



https://doi.org/10.1109/VTC2022-Spring54318.2022.9861002