A free-space time-domain method is proposed to retrieve dielectric constant (<inline-formula> <tex-math notation="LaTeX">\varepsilon _{r} </tex-math></inline-formula>), conductivity (<inline-formula> ...<tex-math notation="LaTeX">\sigma _{e} </tex-math></inline-formula>), and thickness (<inline-formula> <tex-math notation="LaTeX">d </tex-math></inline-formula>) of metal-backed low-loss dielectric samples using calibration-independent reflected power peak measurements. Its algorithm is validated by numerical calculations and simulations (CST Microwave Studio) using a sine-modulated Gaussian window. A sensitivity analysis is followed to examine its performance considering the dependencies of reflected power peaks with respect to <inline-formula> <tex-math notation="LaTeX">\varepsilon _{r} </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">\sigma _{e} </tex-math></inline-formula>. Free-space time-domain measurements have been implemented after transforming frequency-domain measurements into time-domain ones to extract <inline-formula> <tex-math notation="LaTeX">\varepsilon _{r} </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">\sigma _{e} </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">d </tex-math></inline-formula> of polypropylene, polyethylene, and polyoxymethylene samples.
One method of measuring precipitation and wind over the ocean is through analysis of the underwater ambient acoustics. In this study, the ambient ocean noises recorded by a passive aquatic listener ...(PAL) in the Mediterranean are used to compare the effectiveness of the machine learning techniques for measuring the wind speed and precipitation rate with the empirical methods from previous works. The data were collected over the timeframe of June 2011 to May 2012 and included two storms that caused severe coastal flooding in Genoa, Italy. A spar buoy at the surface above the PAL provided high-quality in situ measurements to act as the reference data for model training and validation. The results using the machine learning models show correlation coefficients of 0.95 between the acoustic data and wind speed and a reduction in unexplained variance by over a third from previous methods. For precipitation, CatBoost and random forest models are used to measure the total precipitation for 12 events using leave-one-event-out cross-validation, demonstrating mean errors of 28% and 34% and median errors of 18% and 17%, respectively. The ability to measure wind and precipitation by applying machine learning on data from underwater acoustic recorders shows potential to help improve in situ measurements over oceans globally.
Reconfigurable intelligent surfaces (RISs) provide an interface between the electromagnetic world of wireless propagation environments and the digital world of information science. Simple yet ...sufficiently accurate path loss models for RISs are an important basis for theoretical analysis and optimization of RIS-assisted wireless communication systems. In this paper, we refine our previously proposed free-space path loss model for RISs to make it simpler, more applicable, and easier to use. The impact of the antenna's directivity of the transmitter, receiver, and the unit cells of the RIS on the path loss is explicitly formulated as an angle-dependent loss factor. The refined model gives more accurate estimates of the path loss of RISs comprised of unit cells with a deep sub-wavelength size. Based on the proposed model, the properties of a single unit cell are evaluated in terms of scattering performance, power consumption, and area, which allows us to unveil fundamental considerations for deploying RISs in high frequency bands. Two fabricated RISs operating in the millimeter-wave (mmWave) band are utilized to carry out a measurement campaign. The measurement results are shown to be in good agreement with the proposed path loss model. In addition, the experimental results suggest an effective form to characterize the power radiation pattern of the unit cell for path loss modeling.
On the Uniqueness of FROG Methods Bendory, Tamir; Sidorenko, Pavel; Eldar, Yonina C.
IEEE signal processing letters
24, Issue:
5
Journal Article
Peer reviewed
Open access
The problem of recovering a signal from its power spectrum, called phase retrieval, arises in many scientific fields. One of many examples is ultrashort laser pulse characterization, in which the ...electromagnetic field is oscillating with ~1015 Hz and phase information cannot be measured directly due to limitations of the electronic sensors. Phase retrieval is ill-posed in most of the cases, as there are many different signals with the same Fourier transform magnitude. To overcome this fundamental ill-posedness, several measurement techniques are used in practice. One of the most popular methods for complete characterization of ultrashort laser pulses is the frequency-resolved optical gating (FROG). In FROG, the acquired data are the power spectrum of the product of the unknown pulse with its delayed replica. Therefore, the measured signal is a quartic function of the unknown pulse. A generalized version of FROG, where the delayed replica is replaced by a second unknown pulse, is called blind FROG. In this case, the measured signal is quadratic with respect to both pulses. In this letter, we introduce and formulate FROG-type techniques. We then show that almost all band-limited signals are determined uniquely, up to trivial ambiguities, by blind FROG measurements (and thus also by FROG), if in addition we have access to the signals power spectrum.
The curse of outlier measurements in estimation problems is a well-known issue in a variety of fields. Therefore, outlier removal procedures, which enables the identification of spurious measurements ...within a set, have been developed for many different scenarios and applications. In this paper, we propose a statistically motivated outlier removal algorithm for time differences of arrival (TDOAs), or equivalently range differences (RD), acquired at sensor arrays. The method exploits the TDOA-space formalism and works by only knowing relative sensor positions. As the proposed method is completely independent from the application for which measurements are used, it can be reliably used to identify outliers within a set of TDOA/RD measurements in different fields (e.g., acoustic source localization, sensor synchronization, radar, remote sensing, etc.). The proposed outlier removal algorithm is validated by means of synthetic simulations and real experiments.
An optimization-free method is presented for the retrieval of the individual phases of phaseless antenna measurements in the near-field (NF) zone of an antenna under test (AUT). Based on a bilinear ...expression for the magnitude-only measurements, the result for any desired magnitude-only measurement sample is synthetically calculated as a linear combination of sufficiently many previous measurement samples. In this way, signals, which allow for a straightforward computation of the phase difference between a pair of measurement samples, are obtained. Its high numerical complexity limits the algorithm to problems of moderate size, but understanding and using the algorithm delivers new insight into the phase retrieval problem and allows to evaluate the feasibility of specific measurement procedures and configurations. In particular, we show that there exist at most <inline-formula> <tex-math notation="LaTeX">N_{\mathrm {DOF}}^{2} </tex-math></inline-formula> independent phaseless measurements for an AUT with <inline-formula> <tex-math notation="LaTeX">N_{\mathrm {DOF}} </tex-math></inline-formula> degrees of freedom (DoFs). Any additional phaseless measurement can be calculated as a linear combination of those <inline-formula> <tex-math notation="LaTeX">N_{\mathrm {DOF}}^{2} </tex-math></inline-formula> measurement samples. Under certain circumstances, much less than <inline-formula> <tex-math notation="LaTeX">N_{\mathrm {DOF}}^{2} </tex-math></inline-formula> measurement samples are sufficient to retrieve the magnitude and phase of the measured field at desired locations. A numerical example shows that the presented method is capable, in principle, to reconstruct all relevant NF information needed for a conventional NF far-field transformation (NFFFT) from noiseless irregularly distributed squared magnitude field samples only. In addition, it is shown that measurements with specialized probes can bring more information into the problem than measurements on surfaces with different distances to the AUT. When it comes to true noisy measurement data, the presented method can reconstruct NF magnitudes reliably, but the reconstruction of phase information is sensitive to noise.
The requirements for dielectric measurements on polar liquids lie largely in two areas. First there is scientific interest in revealing the structure of and interactions between the molecules - this ...can be studied through dielectric spectroscopy. Secondly, polar liquids are widely used as dielectric reference and tissue equivalent materials for biomedical studies and for mobile telecommunications, health and safety related measurements. This review discusses these roles for polar liquids and surveys the techniques available for the measurement of their complex permittivity at RF and Microwave frequencies. One aim of the review is to guide researchers and metrologists in the choice of measurement methods and in their optimization. Particular emphasis is placed on the importance of traceability in these measurements to international standards
In this study, a quantum measurement method of radio-frequency (RF) attenuation based on atomic resonance is realized for the first time utilizing the interaction among atoms and RF waves. In the ...experiments, cesium-133 ( 133 Cs) atoms in a rectangular cell inserted in a WR-90 waveguide were simultaneously irradiated with a 9.2-GHz RF wave and an 852-nm wavelength laser. First, double-resonance spectroscopy of the RF waves and laser was performed, and the magnitude and time constant of the double-resonance signals were compared with the attenuation. Subsequently, the Rabi frequency of cesium atoms was measured using an atomic candle method. Results reveal that the Rabi frequency is proportional to the relative RF magnetic field strength. Moreover, the best linearity (up to 35 dB) was obtained for the Rabi frequency-derived attenuation. This study is expected to contribute to the development of RF precision measurement techniques for communication technologies such as 5G/Beyond 5G and electromagnetic compatibility evaluations, as well as to realize the next-generation RF power and attenuation standards based on quantum phenomena.
Laser triangulation on-machine measurement (LTOMM) with associated processing technology is an effective way to evaluate freeform surfaces' quality without removing the workpiece from the machine ...tool. In this article, an integrated system able to acquire the sensor's one-dimensional displacements and three-dimensional locations is presented. This system is able to prevent spatial mismatch, and then a demand-oriented LTOMM process is proposed. Different from conventional understanding of the trade-off behavior between accuracy and efficiency, an error management strategy is formed to fulfil the required accuracy by precisely controlling the inclination angle and measurement displacement. To improve efficiency, these parameters are fine-tuned adaptively to the surface characteristics by an accuracy-monitoring path optimization algorithm (AMPOA) developed. The unevenly distributed peak error is suppressed by utilizing a mathematical model to regulate the measurement path without compromising efficiency. A simulation is conducted to substantiate that this method is not only able to improve measurement efficiency but also to suppress the peak error. The algorithm and the model were verified on a freeform turbine blade surface with a required accuracy of 20 lm. The efficiency was improved by 42.45%, and the peak error was reduced. This would help both the researchers and industries with a more efficient and reverse-controllable demand-oriented LTOMM approach under the constraint of required accuracy in the future.
The presence of asynchronous absolute and relative measurements has posed a great challenge to the current multisensor positioning method in robotic systems. Although traditional factor graph methods ...possess a capability of plug-and-play, only a compromised performance can be obtained when dealing with an increasing number of asynchronous observations. In this article, a novel plug-and-play factor graph method for asynchronous absolute/relative measurements fusion in multisensor positioning is proposed. Different from traditional methods, a fixed-rate graph model is formed. The variable nodes in the graph are built at a fixed update rate to do the optimization, which is not affected by the arrival of measurements. Asynchronous absolute and relative measurements between two successive variable nodes are associated with corresponding variable nodes in the graph via the propagation of closed-form inertial measurement unit (IMU) preintegration. The simulations, datasets, and field tests are carried out to validate the proposed method. The results indicate that the closed-form IMU preintegration method has better dynamic adaptability in fusion system to formulate the association with asynchronous measurements. On this basis, the proposed method can integrate asynchronous measurements in a plug-and-play manner and achieve better performance compared to current methods. Meanwhile, the computational load can also be reduced.
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