Tomographic microwave imaging is employed as a method of nondestructive testing in a wide range of industrial applications, e.g., for quality control. However, many low-permittivity materials, such as gaseous substances or foam with high air content, do not provide sufficient contrast to the environment to be measured with existing systems. This article introduces a 77-79-GHz high-resolution tomography system that facilitates the characterization of materials with relative permittivity close to one and very small attenuation. Fully integrated frequency-modulated continuous-wave radar transceivers are utilized as sensors to reduce the system cost and complexity significantly. The medium-dependent time-of-flight between different radar sensors is evaluated to reconstruct the permittivity distribution inside an area-under-test. To solve the underdetermined inverse problem, two methods based on the Tikhonov regularization and total variation regularization are implemented. Individual impacts on measurement uncertainty are investigated. Custom-designed horn antennas ensure a sufficient number of signal paths between the sensors. A prototype is built using two synchronized radar modules and a rotary stage to emulate a higher number of sensors. System simulations and measurements are conducted utilizing various low-permittivity foam phantoms. Successful reconstructions of the 2-D permittivity distribution demonstrate the feasibility of this approach.

In the last decade there was enormous progress in integrated mm-wave integrated circuit design, targeting primarily mobility applications like automated driving [1], [2]. It is shown in this paper how this progress, paired with advanced signal processing and the enormous increase of available processing power, enables successful implementation of completely different, yet spectacular, applications. The evolution of designs of massive multiple-input multiple-output imaging radars in combination with the associated real-time signal processing and in-line autocalibration for analyzing the burden surface in blast furnaces, the BLASTDAR system, is presented. BLASTDAR systems now operate in all five voestalpine blast furnaces for several years.

Tomographic microwave imaging is employed in numerous industrial applications, e.g., nondestructive testing. However, most existing systems are not suitable for measurements of low-permittivity materials such as gaseous substances or insulating foam with high air content. This paper introduces a 79 GHz high-resolution tomography system enabling characterization of materials with relative permittivity close to one. It is based on fully-integrated frequency-modulated continuous-wave radar transceivers which significantly reduce cost and complexity. A first prototype is built with two radar sensors and a rotary stage to emulate a higher sensor count. The medium-dependent time-of-flight through the area-under-test is evaluated and Tikhonov regularization is applied to solve the inverse problem and reconstruct a 2D image. System simulations and measurements with low-permittivity foam objects confirm the feasibility of this approach.

A primary concern in a multitude of industrial processes is the precise monitoring of gaseous substances to ensure proper operating conditions. However, many traditional technologies are not suitable for operation under harsh environmental conditions. Radar-based time-of-flight permittivity measurements have been proposed as alternative but suffer from high cost and limited accuracy in highly cluttered industrial plants. This paper examines the performance limits of low-cost frequency-modulated continuous-wave (FMCW) radar sensors for permittivity measurements. First, the accuracy limits are investigated theoretically and the Cramér-Rao lower bounds for time-of-flight based permittivity and concentration measurements are derived. In addition, Monte-Carlo simulations are carried out to validate the analytical solutions. The capabilities of the measurement concept are then demonstrated with different binary gas mixtures of Helium and Carbon Dioxide in air. A low-cost time-of-flight sensor based on two synchronized fully-integrated millimeter-wave (MMW) radar transceivers is developed and evaluated. A method to compensate systematic deviations caused by the measurement setup is proposed and implemented. The theoretical discussion underlines the necessity of exploiting the information contained in the signal phase to achieve the desired accuracy. Results of various permittivity and gas concentration measurements are in good accordance to reference sensors and measurements with a commercial vector network analyzer (VNA). In conclusion, the proposed radar-based low-cost sensor solution shows promising performance for the intended use in demanding industrial applications.

In most real-world signal processing and measurement applications, unavoidable measurement noise is one of the key factors that limits overall system performance. To be able to assess the performance of a signal processing system in-situ, noise variance and signal-to-noise ratio, respectively can only be estimated from available measurement data. Furthermore, the statistical performance of these estimates is of importance. While noise variance estimation can be done in theory by simply applying some well-known estimators, this standard approach can fail in many practical applications due to unavoidable modeling inaccuracies. To overcome this, we extend an approach proposed in [1] for noise variance estimation from spectral data using data windows. The only necessary prerequisite for the applicability of the algorithm is the existence of a spectral region containing noise only. By applying robust estimation techniques, even this assumption can be relaxed to some extent. We also analyze the corresponding Cramér-Rao bounds and validate the approach by means of Monte-Carlo simulations. The case of signal-to-noise ratio estimation in sinusoidal models is treated as a special case of particular interest, together with a discussion of the colored noise case and practical application examples. Furthermore, the Cramér-Rao bounds and simulation results are compared with real world measurement results from a radio-acoustic-sounding-system application.

This article discusses compact radio-acoustic-sounding systems (RASSs) for industrial applications.The electromagnetic-acoustic interaction enables to measure temperatures of gases without contact and spatially resolved.For this purpose, the speed of a modulated sound pulse, travelling through the gas with a velocity proportional to the temperature, is determined with a Doppler radar.The optimum sound pulse´s in terms of its frequency is discussed.The so called Bragg condition is essential to obtain sufficient receive power.The two most important conditions for an optimal Bragg reflection are the tuning of the wavelengths and an optimal collocation of the sources.These conditions are calculated numerically and verified with real-world measurement data.One purpose of this paper is to summarize physical effects that are key elements to the function of the RASS.

This article describes a measurement setup for non-contact, spatially resolved temperature measurement of gases. The electromagnetic-acoustic interaction, known from the radio-acoustic-sounding method, makes it possible to measure temperatures continuously in the industrial environment. For this purpose, the speed of sound of an emitted sound pulse, which is temperature-dependent, will be determined with a Doppler radar. The operating principle, a possible setup and its challenges are shown and presented with measurements. Further, it is discussed how air flows or temperatures can be determined multidimensionally with this measuring principle.

Dieser Artikel beschreibt einen Messaufbau für die berührungslose, abstandsaufgelöste Temperaturmessung von Gasen. Die elektromagnetisch-akustische Wechselwirkung, bekannt von der Radio-Acoustic-Sounding Methode, macht es möglich, auch im industriellen Umfeld kontinuierlich Temperaturen zu messen. Dazu wird die Schallgeschwindigkeit, welche in einem eindeutigen Zusammenhang mit der Temperatur steht, mit einem Doppler-Radar bestimmt. Das Funktionsprinzip, ein realisierter Aufbau und dessen Herausforderungen werden aufgezeigt und mit Messungen dargestellt. Weiteres wird diskutiert, wie mit diesem Messprinzip neben der Temperatur auch Luftströmungen mehrdimensional bestimmt werden können.

The main goal of surfacegauging radar applications is to obtain a complete image of a surface area inside a closed and possibly tightly sealed container filled with materials having sufficient reflectivity for highfrequency electromagnetic waves. Radar systems are applicable where standard acoustical or optical measurement techniques are strongly impaired due to harsh environmental conditions-such...

Common algorithms for radar array imaging rely on sufficiently precise calibration before evaluation. A system calibration is necessary to compensate potential unavoidable error sources that decrease the accuracy and reliability of the estimates and worsen the beam pattern of the antenna array. Several calibration methods have been developed, most of them are based on a-priori, i.e., offline measurements with a well defined target scenario. In this paper we present an algorithm that is capable of executing an online self-calibration and image formation for the special case when the target scenario is an arbitrary but continuous surface. The two separated tasks, system calibration followed by image formation, are combined in a single formulation that efficiently solves a minimization problem. Thus, the need for a-priori calibration measurements is avoided. The correct functionality of this algorithm is shown with simulation results for different surface scenarios and spatial dimensions. A possible real-world application in blast furnace burden surface imaging is discussed.

In this paper, we present a radar sensor system for real-time blast furnace burden surface imaging inside a fully operative blast furnace, called BLASTDAR, the blast furnace radar. The designed frequency-modulated continuous-wave (FMCW) radar sensor array operates in the frequency band around 77 GHz and consists of several nonuniformly spaced receive and transmit antennas, making it a multiple-input multiple-output radar system with large aperture. Mechanical steering is replaced by digital array processing techniques. Off-the-shelf automotive-qualified multichannel monolithic microwave integrated circuits are used. By means of this configuration, a virtual antenna array with 256 elements was developed that guarantees the desired angular resolution of better than 3°, and a range resolution of about 15 cm. Based on the single-channel FMCW signal model, this paper will derive a multichannel signal model in combination with a digital beamforming approach and further advanced signal processing algorithms. The implementation of a simulation tool covering the whole design process is shown. Based on these simulation results, a system configuration is chosen and the obtained setup is defined and presented. A description of the manufactured cost-efficient radio frequency and baseband boards together with the housing design shows the practical implementation of the sensor. For the system calibration, two different methods are listed and compared regarding their performance. Verification measurements confirm the predicted performance of the developed sensor. Several measurements inside a fully operational blast furnace demonstrate the proper long-term functionality of the system, to the best of our knowledge, for the first time worldwide. It is in continuous operation since about two years in blast furnace #5 of voestalpine Stahl GmbH, Linz.