Search Results (22)

This article presents an innovative integration of Glow Discharge Detector Focal Plane Arrays (GDD FPA) with Chirped Frequency Modulated Continuous Wave (FMCW) Radar, enhancing millimeter-wave (MMW) imaging. The cost-effective FPA design using GDDs as pixel elements forms the foundation of the system. We investigate MMW effects on GDD discharge currents via basic data acquisition (DAQ) and implement a scanning mechanism with a step motor for sub-pixel imaging. The setup integrates an MMW source, optical components, a timer/counter, and an 8 × 8 FPA with 64 GDD, operating in electrical detection modes and processing signals using Fast Fourier Transform (FFT) algorithms. Recent advancements in millimeter-wave imaging have focused on improving image resolution and acquisition speed through various techniques, including lock-in amplifiers and electrical detection methods. However, these methods introduce complexity, cost, and extended acquisition times. Our approach mitigates these challenges by implementing a simplified FPA design that eliminates the need for external signal conditioning elements, providing faster and more efficient image acquisition. The primary contributions include significant improvements in the speed and automation of image acquisition achieved through a coordinated control mechanism for efficient row scanning. Compared to previous generations of GDD FPAs, this system achieves a notable reduction in image acquisition time by up to 75%, while maintaining high fidelity. These enhancements make the system particularly suitable for time-sensitive applications. Additionally, future research directions include the incorporation of 3D imaging using FMCW radar. Results from the FMCW measurements using the single GDD circuit demonstrate the system’s ability to accurately capture and process MMW radiation, even at low intensities. The combined strengths of GDD FPA and chirped FMCW radar underscore the system’s effectiveness in MMW detection, laying the groundwork for advanced MMW imaging capabilities across diverse applications. Full article

This paper presents a preliminary proof-of-concept study of a novel approach to 3D millimeter-wave (MMW) imaging, demonstrating the first implementation of Glow Discharge Detectors (GDDs) in this domain. GDDs offer significant advantages over conventional MMW detectors like Schottky diodes or bolometers due to their cost-effectiveness, robustness to high-power MMW signals, and reliable operation under diverse environmental conditions. Based on weakly ionized plasma (WIP) technology, GDDs detect changes in discharge current upon MMW exposure, providing an affordable and durable alternative to traditional MMW imaging systems. The system operates within a subset of the W-band (101–109 GHz), utilizing a customized transmitter (Tx 272 from VDI Technologies), which operates at a frequency range proportional to the VCO supply voltage level. The Frequency-Modulated Continuous Wave (FMCW) signal source is split into target and reference paths via a compact waveguide splitter, improving stability and reducing the complexity of the optical setup. Reflected signals are processed by the GDD, which functions as a heterodyne receiver, and Fast Fourier Transform (FFT) is used to extract range data. A 2D grid scanning mechanism, controlled by step motors, maps the surface of the object, while depth information is derived from FMCW frequency differentials to construct a complete 3D profile. This work demonstrates the potential of GDD-based 3D MMW imaging as a low-cost, efficient solution for security screening and industrial inspection. By addressing challenges in cost, scalability, and performance under high-power MMW signals, this approach represents a significant step forward in making MMW imaging technology more accessible, while highlighting the need for further development to achieve practical implementation. Full article

Cementitious materials are susceptible to damage not only from mechanical loading, but also from environmental (physical, chemical, and biological) factors. For Textile-Reinforced Cementitious (TRC) composites, durability poses a significant challenge, and a reliable method to assess long-term performance is still lacking. Among various durability attacks, freeze–thaw can induce internal cracking within the cementitious matrix, and weaken the textile–matrix bond. Such cracks result from hydraulic, osmotic, and crystallization pressure arising from the thermal cycles, leading to a reduction in the stiffness in the TRC composites. Early detection of freeze–thaw deterioration can significantly reduce the cost of repair, which is only possible through periodic, full-field monitoring of the composite. Full-field monitoring provides a comprehensive view of the damage distribution, offering valuable insights into the causes and progression of damage. The crack location, size, and pattern give more information than that offered by single-point measurement. While visual inspections are commonly employed for crack assessment, they are often time-consuming. Technological advances now enable crack pattern classification based on high-quality surface images; however, these methods only provide information limited to the surface. Elastic wave-based non-destructive testing (NDT) methods are highly sensitive to the material’s mechanical properties, and therefore are widely used for damage monitoring. On the other hand, electromagnetic wave-based NDTs offer the advantage of fast, non-contact measurements. Micro- and millimeter wave frequencies offer a balance of high resolution and wave penetration, although they have not yet been sufficiently explored for detecting damage in cementitious composites. In this study, TRC specimens were subjected to up to 150 freeze–thaw cycles and monitored using a combination of active elastic and electromagnetic wave-based NDT mapping methods. For this purpose, transmission measurements were conducted at multiple points, with ultrasonic pulse velocity (UPV) employed as a benchmark and, for the first time, millimeter wave (MMW) spectrometry applied. This multi-modal mapping approach enabled the tracking of damage progression, and the identification of degraded zones. Full article

We review the evolution of our understanding of the planetary nebulae phenomenon and their place in the scheme of stellar evolution. The historical steps leading to our current understanding of central star evolution and nebular formation are discussed. Recent optical imaging, X-ray, ultraviolet, infrared, millimeter wave, and radio observations have led to a much more complex picture of the structure of planetary nebulae. The optically bright regions have multiple shell structures (rims, shells, crowns, and haloes), which can be understood within the interacting winds framework. However, the physical mechanism responsible for bipolar and multipolar structures that emerged during the proto-planetary nebulae phase is yet to be identified. Our morphological classifications of planetary nebulae are hampered by the effects of sensitivity, orientation, and field-of-view coverage, and the fraction of bipolar or multipolar nebulae may be much higher than commonly assumed. The optically bright bipolar lobes may represent low-density, ionization-bounded cavities carved out of a neutral envelope by collimated fast winds. Planetary nebulae are sites of active synthesis of complex organic compounds, suggesting that planetary nebulae play a major role in the chemical enrichment of the Galaxy. Possible avenues of future advancement are discussed. Full article

The transition region is a very thin but most peculiar layer in the solar atmosphere located between the solar chromosphere and the corona. It is a key region for understanding coronal heating, solar eruption triggers, and the origin of solar winds. Here, almost all physical parameters (density, temperature, and magnetic fields) have the maximum gradient. Therefore, this region should be highly dynamic, including fast energy releasing and transporting, plasma heating, and particle accelerating. The physical processes can be categorized into two classes: thermal and non-thermal processes. Thermal processes can be observed at ultraviolet (UV) and extreme ultraviolet (EUV) wavelengths via multi-wavelength images. Non-thermal processes accelerate non-thermal electrons and produce radio emissions via the gyrosynchrotron mechanism resulting from the interaction between the non-thermal electrons and magnetic fields. The frequency range spans from several GHz to beyond 100 GHz, in great number of bursts with narrowband, millisecond lifetime, rapid frequency drifting rates, and being referred to as transition region small-scale microwave bursts (TR-SMBs). This work proposes a new type of Solar Ultra-wide Broadband Millimeter-wave Spectrometer (SUBMS) that can be used to observe TR-SMBs. From SUBMS observations, we can derive rich dynamic information about the transition region, such as information about non-thermal energy release and propagation, the flows of plasma and energetic particles, the magnetic fields and their variations, the generation and transportation of various waves, and the formation and evolution of the source regions of solar eruptions. Such an instrument can actually detect the non-thermal signals in the transition region during no flare as well as the eruptive high-energy processes during solar flares. Full article

Multiple-input multiple-output (MIMO) technology is widely used in the field of security imaging. However, existing imaging systems have shortcomings such as numerous array units, high hardware costs, and low imaging resolutions. In this paper, a sparse array-based frequency modulated continuous wave (FMCW) millimeter wave imaging system, operating in the W-band, is presented. In order to reduce the number of transceiver units of the system and lower the hardware cost, a linear sparse array with a periodic structure was designed using the MIMO technique. The system operates at 70~80 GHz, and the high operating frequency band and 10 GHz bandwidth provide good imaging resolution. The system consists of a one-dimensional linear array, a motion control system, and hardware for signal generation and image reconstruction. The channel calibration technique was used to eliminate inherent errors. The system combines mechanical and electrical scanning, and uses FMCW signals to extract distance information. The three-dimensional (3-D) fast imaging algorithm in the wave number domain was utilized to quickly process the detection data. The 3-D imaging of the target in the near-field was obtained, with an imaging resolution of 2 mm. The imaging ability of the system was verified through simulations and experiments. Full article

In this article, a novel three-dimensional (3-D) imaging method based on the range decomposing algorithm (RDA) is proposed for millimeter wave imaging. We combined it with binomial theory and we derive the theoretical formulation of RDA applied to single-input–single-output (SISO)/multiple-input–multiple-output (MIMO) array; meanwhile, its computational complexity and computational error are analyzed. Compared to the classical Fourier algorithm, such as the range migration algorithm (RMA) and the phase shift migration (PSM), the proposed algorithm can replace the time-consuming interpolation and accumulation operations with reasonable approximations and transformations offering a more efficient approach, while maintaining the image quality. In addition, a method based on RDA which is applicable to the transformation between MIMO and SISO, is proposed to further enhance the processing efficiency. Proof-of-principle simulation using echo data collected from a large number of antennas, verifies that the proposed algorithm has higher efficiency. In order to better verify the feasibility of the proposed algorithm, a scanning prototype located in the millimeter wave band is designed. The experimental results of different targets demonstrate that the proposed algorithm achieves significantly higher reconstruction efficiency when compared to the traditional algorithms. Full article

In this study, a laser interferometric sensing measurement (ISM) system based on a 4R manipulator system is developed to achieve detection of mechanical targets, which aims to realize the real-time, online detection of workpieces with high precision during processing. The 4R mobile manipulator (MM) system is flexible and can move in the workshop, aiming to preliminarily track the position of the workpiece to be measured and locate it at millimeter level. The reference plane of the ISM system is driven by piezoelectric ceramics with the spatial carrier frequency realized and the interferogram obtained by a charge coupled device (CCD) image sensor. The subsequent processing of the interferogram includes fast Fourier transform (FFT), spectrum filtering, phase demodulation, tilt elimination for wave-surface, etc., so as to further restore the surface shape of the measured surface and obtain the surface quality indexes. A novel cosine banded cylindrical (CBC) filter is used to improve the FFT processing accuracy, and a bidirectional extrapolation and interpolation (BEI) technique is proposed for the preprocessing operation of real-time interferograms before FFT processing. Compared with the results from a ZYGO interferometer, the real-time online detection results show the reliability and practicability of this design. The relative error of peak–valley value reflecting the processing accuracy can reach about 0.63%, with the root-mean-square value reaching about 1.36%. Some possible applications of this work include the surface of mechanical parts in the process of online machining, the end face of shaft-like structures, annular surfaces, etc. Full article

The relatively high atmospheric propagation of millimeter-waves (MMW) was found to be one of the most critical reasons for the development of reliable sensors for MMW detection. According to previous research works, it has been already shown that incident MMW radiation on a glow discharge detector (GDD) can increase the discharge current. Hence, the electrical mode of detection can be employed to detect the presence of MMW radiation. In this article, a new design of a row detector using GDDs as pixel elements, and the influence of MMW incidence on GDD’s discharge current, were acquired using an elementary data acquisition (DAQ) platform. The DAQ system computes the averaged Fast Fourier Transform (FFT) spectrum of the time signal and returns the FFT results as magnitude based on the level of detection. An FFT-based signal acquisition proved to be a better alternative to the lock-in detection that was commonly used in MMW detection systems. This improved detection circuit provides enhanced noise filtering, thereby resulting in better MMW images within a short time. The overhead expense of the entire system is very low, as it can avoid lock-in amplifier stages that were previously used for signal enhancement. A scanning mechanism using a motorized translation stage (step motor) is involved to place and align the row detector in the image plane. The scanning can be carried out vertically to perform the imaging, by configuring the step motor after selecting the desired step size and position. A simplified version of the MMW detection circuit with a dedicated over-voltage protection facility is presented here. This made the detection system more stable and reliable during its operation. The MMW detection circuit demonstrated in this work was found to be a milestone to develop larger focal plane arrays (FPA) with very inexpensive sensor elements. Full article

Due to the increasing demand for fast data rates and large spectra, millimeter-wave technology plays a vital role in the advancement of 5G communication. The idea behind Mm-Wave communications is to take advantage of the huge and unexploited bandwidth to cope with future multigigabit-per-second mobile data rates, imaging, and multimedia applications. In Mm-Wave systems, digital precoding provides optimal performance at the cost of complexity and power consumption. Therefore, hybrid precoding, i.e., analog–digital precoding, has received significant consideration as a favorable alternative to digital precoding. The conventional methods related to hybrid precoding suffer from low spectral efficiency and large processing time due to nested loops and the number of iterations. A manifold optimization-based algorithm using the gradient method is proposed to increase the spectral efficiency to be near optimal and to speed up the processing speed. A comparison of performances is shown using the simulation outcomes of the proposed work and those of the existing techniques. Full article

For millimeter-wave (MMW) imaging security systems, the image resolution promisingly determines the performance of suspicious target detection and recognition. Conventional synthetic aperture radar (SAR) imaging algorithms only provide limited resolution in active MMW imaging, which is limited by the system. In terms of enhancing the resolution of a region of interest (ROI) image containing suspicious targets, super-resolution (SR) imaging is adopted via Bayesian compressive sensing (BCS) implemented by fast Fourier transform (FFT). The spatial sparsity of MMW ROI images is well exploited with BCS to achieve resolution enhancement without computational cost. Both simulated and measured experiments confirm that the proposed scheme effectively improves the resolution of ROI images. Full article

Tin diselenide (SnSe₂) is a layered semiconductor with broad application capabilities in the fields of energy storage, photocatalysis, and photodetection. Here, we correlate the physicochemical properties of this van der Waals semiconductor to sensing applications for detecting chemical species (chemosensors) and millimeter waves (terahertz photodetectors) by combining experiments of high-resolution electron energy loss spectroscopy and X-ray photoelectron spectroscopy with density functional theory. The response of the pristine, defective, and oxidized SnSe₂ surface towards H₂, H₂O, H₂S, NH₃, and NO₂ analytes was investigated. Furthermore, the effects of the thickness were assessed for monolayer, bilayer, and bulk samples of SnSe₂. The formation of a sub-nanometric SnO₂ skin over the SnSe₂ surface (self-assembled SnO₂/SnSe₂ heterostructure) corresponds to a strong adsorption of all analytes. The formation of non-covalent bonds between SnO₂ and analytes corresponds to an increase of the magnitude of the transferred charge. The theoretical model nicely fits experimental data on gas response to analytes, validating the SnO₂/SnSe₂ heterostructure as a suitable playground for sensing of noxious gases, with sensitivities of 0.43, 2.13, 0.11, 1.06 [ppm]⁻¹ for H₂, H₂S, NH₃, and NO_2, respectively. The corresponding limit of detection is 5 ppm, 10 ppb, 250 ppb, and 400 ppb for H₂, H₂S, NH₃, and NO_2, respectively. Furthermore, SnSe₂-based sensors are also suitable for fast large-area imaging applications at room temperature for millimeter waves in the THz range. Full article

Passive millimeter wave has been employed in security inspection owing to a good penetrability to clothing and harmlessness. However, the passive millimeter wave images (PMMWIs) suffer from low resolution and inherent noise. The published methods have rarely improved the quality of images for PMMWI and performed the detection only based on PMMWI with bounding box, which cause a high rate of false alarm. Moreover, it is difficult to identify the low-reflective non-metallic threats by the differences in grayscale. In this paper, a method of detecting concealed threats in human body is proposed. We introduce the GAN architecture to reconstruct high-quality images from multi-source PMMWIs. Meanwhile, we develop a novel detection pipeline involving semantic segmentation, image registration, and comprehensive analyzer. The segmentation network exploits multi-scale features to merge local and global information together in both PMMWIs and visible images to obtain precise shape and location information in the images, and the registration network is proposed for privacy concerns and the elimination of false alarms. With the grayscale and contour features, the detection for metallic and non-metallic threats can be conducted, respectively. After that, a synthetic strategy is applied to integrate the detection results of each single frame. In the numerical experiments, we evaluate the effectiveness of each module and the performance of the proposed method. Experimental results demonstrate that the proposed method outperforms the existing methods with 92.35% precision and 90.3% recall in our dataset, and also has a fast detection rate. Full article

We present a rotational terahertz imaging system for inline nondestructive testing (NDT) of press sleeves for the paper industry during fabrication. Press sleeves often consist of polyurethane (PU) which is deposited by rotational molding on metal barrels and its outer surface mechanically processed in several milling steps afterwards. Due to a stabilizing polyester fiber mesh inlay, small defects can form on the sleeve’s backside already during the initial molding, however, they cannot be visually inspected until the whole production processes is completed. We have developed a fast-scanning frequenc-modulated continuous wave (FMCW) terahertz imaging system, which can be integrated into the manufacturing process to yield high resolution images of the press sleeves and therefore can help to visualize hidden structural defects at an early stage of fabrication. This can save valuable time and resources during the production process. Our terahertz system can record images at 0.3 and 0.5 THz and we achieve data acquisition rates of at least 20 kHz, exploiting the fast rotational speed of the barrels during production to yield sub-millimeter image resolution. The potential of automated defect recognition by a simple machine learning approach for anomaly detection is also demonstrated and discussed. Full article

Millimeter-wave (W-band) radar measurements were taken for two maritime targets instrumented with attitude and heading reference systems (AHRSs) in a littoral environment with the aim of developing a multiaspect classifier. The focus was on resource-limited implementations such as short-range, tactical, unmanned aircraft systems (UASs) and dealing with limited and imbalanced datasets. Radar imaging and preprocessing consisted of recording high-resolution range profiles (HRRPs) and performing range alignment using peak detection and fast Fourier transforms (FFTs). HRRPs were used because of their simplicity, reliability, and speed. The features used were fixed-length, frequency domain range profiles. Two linear support vector machine (SVM)-based classifiers were developed which both yielded excellent results in their general forms and were simple to implement. The first approach utilized the positive predictive value (PPV) and negative predictive value (NPV) statistics of the SVM directly to generate target probabilities and consequently determine the optimal aspect transitions for classification. The second approach used the Kolmogorov–Smirnov test for dimensionality reduction, followed by concatenating feature vectors across several aspects. The latter approach is particularly well-suited to resource-constrained scenarios, potentially allowing for retraining and updating in the field. Full article