Zeitschriftenaufsätze

Hochpräzise Wägesysteme nach dem Prinzip der elektromagnetischen Kraftkompensation (EMK), wie Massekomparatoren, finden trotz Neudefinition der Einheit Kilogramm weiterhin Anwendung bei der Realisierung sowie Weitergabe einer praktischen Masseskale, indem sie metrologische Massevergleiche anhand des elektrischen Stromes als Zwischengröße ermöglichen. Gleichzeitig haben Quanteninterferometer auf Basis einer supraleitenden Hochgeschwindigkeitselektronik das Potential, kleinste Änderungen des magnetischen Flusses im Femtotesla-Bereich aufzulösen und eröffnen somit einen alternativen Ansatz zum Erfassen kleinster Stromdifferenzen. Die Kombination dieser bislang größtenteils nur für Fundamentalexperimente in der elektrischen Metrologie ausgenutzten quantenelektrischen Effekte mit Systemen der Präzisionskraftmessung ist eine neuartige Ausgangsbasis zur Verbesserung der Messgenauigkeit dieser Referenzsysteme. Insbesondere bietet die Anwendung eines quantenbasierten Analog-zu-Digital-Wandlers ein deutliches Potential zum Erschließen bisher unerreichter Genauigkeiten. In diesem Beitrag werden die Ergebnisse erster experimenteller Arbeiten zum Nachweis des grundlegenden Funktionsprinzips präsentiert. Darüber hinaus erfolgt eine Abschätzung der Leistungsfähigkeit sowie des Entwicklungspotentials des vorgestellten quantenbasierten Stromsensors für hochpräzise EMK-Wägesysteme.

In this paper, the Tensor-Based Near-Field Localization (TeNFiLoc) algorithm is proposed for channel estimation and user localization on the uplink of a multi-carrier wireless communication system with a massive antenna array. OFDM is used as the modulation scheme and the user can be located in the near-field of the array. The exact spherical model of the impinging wavefronts allows TeNFiLoc to localize and identify the reflected paths and distinguish them from the Line-of-Sight (LoS) path. Some additional processing generally allows TeNFiLoc to localize user even in non-LoS scenarios, when the LoS path may be blocked or shadowed, provided that the number of reflected paths that reach the receiver is not less than three. It is also shown that perfect knowledge of the transmitted data is not necessarily required to perform channel estimation and user localization. Using a specific design of the transmitted signal, an additional low throughput, highly reliable communication link to the receiver can be established. Simulation results demonstrate the excellent localization accuracy of the TeNFiLoc algorithm and its applicability in practical scenarios.

In ultrasound nondestructive testing (NDT), a widespread approach is to take synthetic aperture measurements from the surface of a specimen to detect and locate defects within it. Based on these measurements, imaging is usually performed using the synthetic aperture focusing technique (SAFT). However, SAFT is suboptimal in terms of resolution and requires oversampling in the time domain to obtain a fine grid for the delay-and-sum (DAS). On the other hand, parametric reconstruction algorithms give better resolution, but their usage for imaging becomes computationally expensive due to the size of the parameter space and a large amount of measurement data in realistic 3-D scenarios when using oversampling. In the literature, the remedies to this are twofold. First, the amount of measurement data can be reduced using state-of-the-art sub-Nyquist sampling approaches to measure Fourier coefficients instead of time-domain samples. Second, parametric reconstruction algorithms mostly rely on matrix-vector operations that can be implemented efficiently by exploiting the underlying structure of the model. In this article, we propose and compare different strategies to choose the Fourier coefficients to be measured. Their asymptotic performance is compared by numerically evaluating the Cramér-Rao bound (CRB) for the localizability of the defect coordinates. These subsampling strategies are then combined with an l1-minimization scheme to compute 3-D reconstructions from the low-rate measurements. Compared to conventional DAS, this allows us to formulate a fully physically motivated forward model matrix. To enable this, the projection operations of the forward model matrix are implemented matrix-free by exploiting the underlying two-level Toeplitz structure. Finally, we show that high-resolution reconstructions from as low as a single Fourier coefficient per A-scan are possible based on simulated data and measurements from a steel specimen.

The 5th generation new radio (5G NR) standards create both enormous challenges and potential to address the spatio-spectral-temporal agility of wireless transmission. In the framework of a research unit at TU Ilmenau, various concepts were studied, including both approaches toward integrated circuits and distributed receiver front-ends (FEs). We report here on the latter approach, aiming at the proof-of-principle of the constituting FEs suitable for later modular extension. A millimeter-wave agile multi-beam FE with an integrated 4 by 1 antenna array for 5G wireless communications was designed, manufactured, and verified by measurements. The polarization is continuously electronically adjustable and the directions of signal reception are steerable by setting digital phase shifters. On purpose, these functions were realized by analog circuits, and digital signal processing was not applied. The agile polarization is created inside the analog, real-time capable FE in a novel manner and any external circuitry is omitted. The microstrip patch antenna array integrated into this module necessitated elaborate measurements within the scope of FE characterization, as the analog circuit and antenna form a single entity and cannot be assessed separately. Link measurements with broadband signals were successfully performed and analyzed in detail to determine the error vector magnitude contributions of the FE.

Microwave sensors have recently been introduced as high-temporal resolution sensors, which could be used in the contactless monitoring of artery pulsation and breathing. However, accurate and efficient signal processing methods are still required. In this paper, the matrix pencil method (MPM), as an efficient method with good frequency resolution, is applied to back-reflected microwave signals to extract vital signs. It is shown that decomposing of the signal to its damping exponentials fulfilled by MPM gives the opportunity to separate signals, e.g., breathing and heartbeat, with high precision. A publicly online dataset (GUARDIAN), obtained by a continuous wave microwave sensor, is applied to evaluate the performance of MPM. Two methods of bandpass filtering (BPF) and variational mode decomposition (VMD) are also implemented. In addition to the GUARDIAN dataset, these methods are also applied to signals acquired by an ultra-wideband (UWB) sensor. It is concluded that when the vital sign is sufficiently strong and pure, all methods, e.g., MPM, VMD, and BPF, are appropriate for vital sign monitoring. However, in noisy cases, MPM has better performance. Therefore, for non-contact microwave vital sign monitoring, which is usually subject to noisy situations, MPM is a powerful method.