Positioning with medium frequency R-Mode. - In: Navigation, ISSN 2161-4296, Bd. 68 (2021), 4, S. 829-841
R-Mode is a terrestrial navigation system under development for the maritime domain that provides backup in case of a GNSS outage. This paper describes the first test results for real-time positioning on board a ship using medium frequency R-Mode signals. The estimation and positioning algorithms used are described in detail and it is shown how they are integrated into the R-Mode receiver developed by the German Aerospace Center. Moreover, during two daytime experiments with lower and higher dynamic movements of a ship in the Baltic Sea, we were able to achieve a 95% horizontal positioning accuracy of better then 12 m in the center of three R-Mode transmitters. This demonstrates the first time that the medium frequency R-Mode has provided positioning at sea.
Frequency subsampling of ultrasound nondestructive measurements: acquisition, reconstruction, and performance. - In: IEEE transactions on ultrasonics, ferroelectrics, and frequency control, ISSN 1525-8955, Bd. 68 (2021), 10, S. 3174-3191
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.
Agile multi-beam front-end for 5G mm-wave measurements. - In: International journal of microwave and wireless technologies, ISSN 1759-0795, Bd. 13 (2021), 7, S. 740-750
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.
MNP-enhanced microwave medical imaging by means of pseudo-noise sensing. - In: Sensors, ISSN 1424-8220, Bd. 21 (2021), 19, 6613, insges. 23 S.
Matrix pencil method for vital sign detection from signals acquired by microwave sensors. - In: Sensors, ISSN 1424-8220, Bd. 21 (2021), 17, 5735, insges. 24 S.
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.
IEEE access special section editorial: millimeter-wave and terahertz propagation, channel modeling, and applications. - In: IEEE access, ISSN 2169-3536, Bd. 9 (2021), S. 67660-67666
The demand for ever-increasing wireless data transmission rates and throughput area-densities, especially with regard to microcellular networks, internet access, back-hauling, inter-device transmission, and sensing applications, has spurred the exploration of new spectra in the millimeter-wave (30-300 GHz) and terahertz bands (0.1-10 THz), and the study of techniques for multi-Gigabit transmission based on very high-gain antennas [items 1) and 2) in the Appendix].
Locally optimal subsampling strategies for full matrix capture measurements in pipe inspection. - In: Applied Sciences, ISSN 2076-3417, Bd. 11 (2021), 9, 4291, insges. 14 S.
In ultrasonic non-destructive testing, array and matrix transducers are being employed for applications that require in-field steerability or which benefit from a higher number of insonification angles. Having many transmit channels, on the other hand, increases the measurement time and renders the use of array transducers unfeasible for many applications. In the literature, methods for reducing the number of required channels compared to the full matrix capture scheme have been proposed. Conventionally, these are based on choosing the aperture that is as wide as possible. In this publication, we investigate a scenario from the field of pipe inspection, where cracks have to be detected in specific areas near the weld. Consequently, the width of the aperture has to be chosen according to the region of interest at hand. On the basis of ray-tracing simulations which incorporate a model of the transducer directivity and beam spread at the interface, we derive application specific measures of the energy distribution over the array configuration for given regions of interest. These are used to determine feasible subsampling schemes. For the given scenario, the validity/quality of the derived subsampling schemes are compared on the basis of reconstructions using the conventional total focusing method as well as sparsity driven-reconstructions using the Fast Iterative Shrinkage-Thresholding Algorithm. The results can be used to effectively improve the measurement time for the given application without notable loss in defect detectability.
Improving the performance of a radio-frequency localization system in adverse outdoor applications. - In: EURASIP journal on wireless communications and networking, ISSN 1687-1499, (2021), 123, insges. 26 S.
In outdoor RF localization systems, particularly where line of sight can not be guaranteed or where multipath effects are severe, information about the terrain may improve the position estimate's performance. Given the difficulties in obtaining real data, a ray-tracing fingerprint is a viable option. Nevertheless, although presenting good simulation results, the performance of systems trained with simulated features only suffer degradation when employed to process real-life data. This work intends to improve the localization accuracy when using ray-tracing fingerprints and a few field data obtained from an adverse environment where a large number of measurements is not an option. We employ a machine learning (ML) algorithm to explore the multipath information. We selected algorithms random forest and gradient boosting; both considered efficient tools in the literature. In a strict simulation scenario (simulated data for training, validating, and testing), we obtained the same good results found in the literature (error around 2 m). In a real-world system (simulated data for training, real data for validating and testing), both ML algorithms resulted in a mean positioning error around 100 ,m. We have also obtained experimental results for noisy (artificially added Gaussian noise) and mismatched (with a null subset of) features. From the simulations carried out in this work, our study revealed that enhancing the ML model with a few real-world data improves localizations overall performance. From the machine ML algorithms employed herein, we also observed that, under noisy conditions, the random forest algorithm achieved a slightly better result than the gradient boosting algorithm. However, they achieved similar results in a mismatch experiment. This works practical implication is that multipath information, once rejected in old localization techniques, now represents a significant source of information whenever we have prior knowledge to train the ML algorithm.
Estimation bounds of beat signal in the R-mode localization system. - In: IEEE access, ISSN 2169-3536, Bd. 9 (2021), S. 69278-69286
The R-Mode system is a terrestrial navigation system currently under development, which exploits existing means of medium frequency radio transmission. The positioning and timing performance depends on the estimation of the signals' phase offset, from which the ranging information is derived. For an analogous problem such as the single-tone phase estimation, the Cramér-Rao bound (CRB) describes the minimal achievable performance in the mean squared error sense. For R-Mode, the problem involves the estimation of the phase offset for a beat signal, which can be described as the difference of phase estimation for the two aiding carriers next to the signal. This estimates are not statistically independent for finite observation, as we show in this paper. The effect becomes stronger for short observation times, which are important for a near real time application. In this contribution, we are interested in phase offset estimation for the signal models relevant to R-Mode: a beat signal and a beat signal combined with an MSK signal. A closed-form lower CRB is proposed for the aforementioned signal models phase estimation, as well as a generalization of the bound for the phase-difference estimation. Based on this derivation, optimized bit sequences are shown to improve performance of the estimates. The validity of the proposal is verified based on a simulation setup. Measurements acquired during a measurement campaign serve to further justify the usefulness of the bound. Some possible applications of such a bound are R-Mode coverage prediction and the associated phase estimators' performance.
A framework for developing algorithms for estimating propagation parameters from measurements. - In: 2020 IEEE Globecom workshops (GC Wkshps), (2020), insges. 6 S.
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.