Search Results (704)

This paper presents a 67–110 GHz millimeter-wave RF front end for 6G high-speed wireless communications. A broadband diplexer based on a staggered branch-waveguide structure is first proposed to achieve low insertion loss and high isolation simultaneously. The fabricated diplexer exhibits better than 12 dB return loss, 48.6% fractional bandwidth, and less than 1.5 dB insertion loss. A filtering waveguide-to-microstrip transition is then developed to suppress harmonics and spurious signals while maintaining efficient mode conversion. Back-to-back measurements demonstrate over 50 dB out-of-band suppression at 99.5 GHz with a center frequency of 89 GHz. Finally, the proposed components are integrated with broadband amplifiers, filters, and a local oscillator to realize a 67–110 GHz RF front end with 4–26 GHz IF output. Experimental results show harmonic suppression better than 60 dBc, demonstrating excellent spectral purity and validating the proposed architecture as a compact, broadband, and highly integrated solution for future millimeter-wave and terahertz communication systems. Full article

Passive localization of broadband impulsive sources in shallow water is particularly challenging when using a single hydrophone, especially over a sloping seabed. This study presents a novel single-hydrophone localization method for broadband impulsive sources in sloping shallow water. The approach utilizes warping-transformed eigenfrequencies derived from the energy density function of received signals. A key innovation is the method’s capability for simultaneous range and depth estimation in sloping seabed environments, achieved through eigenfrequency pattern matching for range estimation and normalized amplitude matching for depth estimation. The method depends primarily on waveguide depth and average sound speed, enabling robust estimation while exhibiting inherent insensitivity to variations in other environmental parameters. Both simulated and experimental data from a winter sea trial in the East China Sea validate the performance of this dual-parameter estimation approach. The results demonstrate practical applicability for underwater acoustic monitoring and remote sensing in challenging shallow water environments with complex seabed topography. Full article

Strong broadband noise can mask the weak impact responses produced by bearing faults, while wavelet reconstructions selected only by signal-domain scores may not provide useful inputs for diagnosis. To address this problem, this paper presents WPMSR-1D-ResNet, a training-aware wavelet-domain controlled-noise augmentation framework. PKPM-guided particle swarm optimization first generates scale-specific perturbation candidates in the DWT detail coefficients. Signal-fidelity constraints remove distorted reconstructions, and a proxy CNN with identity fallback selects a global candidate according to validation Macro-F1. The final 1D-ResNet is trained jointly with the measured waveform and the selected augmented view, whereas inference uses only the raw signal. Under one fixed data construction and a common fixed 20-epoch budget, WPMSR-1D-ResNet achieved $0.8311\pm 0.0607$ Macro-F1 at the predefined CWRU low-SNR endpoint and ranked third among eleven methods, placing it within the leading statistical group. Its paired mean exceeded raw-signal 1D-ResNet and per-slice PKPM replacement by 0.05582 and 0.05227, respectively, with gains in nine of ten paired computational seeds. Mixed-SNR training increased mean Macro-F1 across eight mismatched-noise conditions from $0.5463\pm 0.1320$ to $0.6105\pm 0.1292$. The method ranked second on PU and third on acquisition-held-out AT data; on AT, it reduced the normal-state false-alarm rate from 0.2854 to 0.1646 while maintaining 0.9708 fault sensitivity. Raw-only inference required 0.266 ms per slice. WPMSR-1D-ResNet, therefore, aligns wavelet augmentation with diagnostic performance, preserves useful waveform information, and removes wavelet reconstruction and PSO from the deployment path. Full article

Improving the performance of computer networks using seamless Wi-Fi can be achieved by implementing a number of strategies and technologies. Strategies include, first of all, the optimal location of routers and access points, the use of a multi-band network or routers supporting different bands. Routers with support for beamforming technology, which directs the Wi-Fi signal directly to connected devices, allow you to improve the signal quality and data transfer speed. Increasing the performance of Wi-Fi computer networks is also provided by the use of network monitoring and management software, which allows you to monitor its performance and respond to possible problems in the network infrastructure. This is an important task, because it determines the quality and convenience of access to network resources. First of all, it allows you to achieve a high data transfer rate, which is especially important in conditions of high traffic necessary for demanding applications. Seamless Wi-Fi technologies also promote increased mobility and flexibility of users, allowing them to connect to the network in any place with a good signal without having to use wired connections. Network management becomes more efficient with automatic switching between access points and increased fault tolerance in the face of changing traffic usage scales. Quantitative results: Implementation of the Wi-Fi roaming mechanism using the IEEE 802.11 specification; Wi-Fi performance measurements obtained for various IEEE 802.11n HT20 and IEEE 802.11a client ratios; the original test environment included 50 laptops and netbooks from various manufacturers, equipped with various operating systems and wireless network adapters; seamless Wi-Fi technologies based on IEEE 802.11k, IEEE 802.11v, and IEEE 802.11r improve communication continuity during device mobility and support real-time AI-based decision making; Wi-Fi based on local communication standards (WLAN-Wireless Local Area Network). It allows data transmission speeds from 1 Mb∙s⁻¹ to 6.75 Gb∙s⁻¹. Indoors, the Wi-Fi range is 20 m, and outdoors 100 m; WiMax (Worldwide Interoperability for Microwave Access) is a built-in set of wireless broadband standards that provide a constant data rate of 1 Gb∙s⁻¹ and 100 Mb∙s⁻¹ in a cellular network; LR-WPANs (Low-Rate Wireless Personal Area Networks) are standards that are the basis for higher communication protocols, ZigBee. They offer data rates ranging from 40 kb to 250 kb∙s⁻¹. In devices with limited resources, these standards operate at 2.4 GHz at higher transmission speeds and 868/915 MHz at lower. The novelty in the article is the implementation of the Wi-Fi roaming mechanism, presentation of Wi-Fi scenarios, discussion of module generations, indication of integrated agriculture in terms of modern digitalization technologies, and characteristics of smart farming. Full article

This article reviews soft clipping, a non-linear amplitude response of IEPE/ICP sensors, which occurs when the internal electronics of an IEPE/ICP sensor exceed their specified linear operating range, typically corresponding to an output of $\pm 5 \mathrm{V}$. Because most measurement systems allow a wider voltage range of $\pm 10 \mathrm{V}$, this non-linear behavior can occur without triggering system-level warnings. Shaker tests indicate that prolonged operation beyond the rated measurement range results in significant signal distortion, particularly attenuating negative acceleration values and producing asymmetric signals. Even after returning to nominal operating conditions, a recovery time of several seconds is required. While the soft clipping effect appears largely frequency independent up to 5 kHz, it may be difficult to detect in real-world vibration tests with complex, broadband signals. Impact tests further reveal that soft clipping subtly affects shock responses, primarily altering initial peaks and potentially obscuring high-frequency modes that decay rapidly. In contrast, frequency-domain analyses are less affected. Overall, the findings emphasize that avoiding operation outside the rated measurement range and implementing appropriate monitoring or warning strategies are essential for reliable IEPE/ICP measurements, especially for time-domain analysis methods. Full article

Vegetation indices (VIs) are widely used as efficient proxies for canopy structure and pigment dynamics, whereas solar-induced chlorophyll fluorescence (SIF) provides a direct indicator of photosynthetic activity. Accurate monitoring of these variables is essential for ecosystem assessment, agricultural management, and satellite product validation. However, long-term field spectroscopy is often influenced by instrument aging and environmental variability, altering radiometric calibration coefficients and introducing uncertainty. In this study, we systematically evaluated the impact of interannual calibration coefficients derived in 2023 and 2024 on six commonly used VIs and SIF. These variables were retrieved from ground-based hyperspectral observations acquired continuously using FLAME-T and QEPRO+ spectrometers over a full rice-growing season. Furthermore, MODIS-like broadband indices were simulated through spectral convolution with sensor response functions. Results revealed clear interannual differences in calibration coefficients, particularly in the blue (450–500 nm) and red-edge (700–800 nm) regions. PRI exhibited the highest sensitivity to calibration changes. SIF also showed pronounced sensitivity due to its intrinsically weak signal and strong channel dependence. Conversely, NDVI and ARVI were highly robust, with the calibration-induced bias of NDVI remaining near zero, benefiting from its normalized formulation and strong near-infrared reflectance. Broadband simulation modified the propagation of uncertainty in an index-dependent manner. Compared with narrowband counterparts, broadband EVI, SAVI, and PRI showed reduced sensitivity, whereas NDVI exhibited a slight sensitivity increase. These findings demonstrate a hierarchy of calibration sensitivity governed by signal strength, spectral band selection, and algorithm design. They emphasize the necessity of frequency-dependent calibration strategies for reliable products in satellite validation studies. Full article

Broadband direction-of-arrival (DOA) estimation using a single acoustic vector sensor (AVS) is an important problem in passive underwater source localization and underwater acoustic signal processing, especially for compact underwater platforms and passive acoustic monitoring applications. However, conventional grid-based sparse Bayesian learning (SBL) may suffer from grid mismatch when the true bearing lies between adjacent predefined grid points. Although a dense grid can reduce this mismatch, it increases computational cost and dictionary coherence. To address this problem, this paper proposes an acoustic-intensity-guided local grid-refinement SBL method, termed AI-LGR-SBL. The pressure and particle-velocity channels are first used to construct acoustic intensity information and detect candidate source regions. The coarse bearing results then guide target-related spectral peak selection during SBL iterations, and local grid refinement is performed only around the selected directions. Simulations involving single-source and two-source scenarios show that AI-LGR-SBL yields sharper spatial spectra and lower estimation errors than conventional grid-based SBL. Compared with basic SBL, AI-LGR-SBL reduces the RMSE by approximately 10% in the low-SNR region and by 4–7% at relatively high SNRs. Compared with globally dense-grid SBL, it reduces the average runtime by approximately 47.3% and 43.6% in the single-source and equal-power two-source scenarios, respectively. Lake-trial data further demonstrate clear bearing–time trajectories and effective sub-grid peak refinement, supporting the feasibility of the proposed method for broadband underwater DOA estimation and passive source localization using a single AVS. Full article

Orthogonal frequency division multiplexing (OFDM) is widely used in broadband wireless communication systems because of its high spectral efficiency, flexible subcarrier allocation, and robustness against frequency-selective fading. However, the high peak-to-average power ratio (PAPR) of OFDM signals reduces the power efficiency of high-power amplifiers and may introduce nonlinear distortion. To address this problem, this paper proposes a multiplier-free Dual-Hadamard PAPR-reduction architecture. The term multiplier-free refers to the additional precoding and phase-weighting operations introduced by the proposed PAPR reduction module, excluding the common OFDM FFT/IFFT operations. Specifically, the proposed architecture combines fast Walsh–Hadamard transform (FWHT) precoding, interleaved partitioning (ILP), and Hadamard-based partial transmit sequence (H-PTS) weighting. Since the FWHT matrix and the H-PTS phase codebook contain only binary signs, the main additional operations are implemented by additions, subtractions, and sign inversions. Simulation results demonstrate that the proposed method reduces the PAPR relative to conventional OFDM without degrading the system’s bit error rate (BER) performance in an additive white Gaussian noise (AWGN) channel when the side information is recovered correctly. Full article

This paper presents a compact, ultra-wideband (UWB) antenna designed for low-power wireless systems requiring upper WLAN (5.725–5.825 GHz) interference mitigation. The antenna integrates a tapered-slot radiator for broadband impedance matching with a dual C-shaped slot resonator on the ground plane to achieve targeted signal rejection. By leveraging the resonant properties of the slots, interference from the WLAN band is suppressed without requiring any active components, ensuring zero additional power consumption for the filtering function. The fabricated prototype, with a compact size of 31 × 40 mm², demonstrates an operational bandwidth from 2.68 to 16 GHz (S11 < −10 dB) with a stable peak realized gain of 2–10 dB and a radiation efficiency above 80% across the passband. At the notch center frequency of 5.72 GHz, the gain decreases by 6.4 dB and the radiation efficiency falls to 0.6, there is effective signal rejection in the target notch band, and there are stable, omnidirectional H-plane radiation patterns. The reflection coefficient at the notch frequency rises to approximately −2.2 dB, effectively suppressing radiation in the WLAN band while maintaining stable gain and omnidirectional patterns in the remaining UWB spectrum. The proposed design offers a simple, low-cost, and energy-efficient solution for achieving spectral coexistence in power-constrained UWB applications. Full article

The Crab pulsar produces extremely intense, short-duration radio bursts known as giant pulses (GPs). We introduce a cumulative-energy diagnostic to quantify the apparent spectral extent of individual Crab giant pulses across the ultra-wideband low-frequency (UWL) receiver band, aiming to build a reproducible method for describing the frequency-domain concentration of emission and to characterize the observed spectral diversity of Crab GPs. Using UWL receiver on the Murriyang (Parkes) radio telescope, we present a systematic study of GPs from the Crab pulsar (PSR J0534+2200). We introduce an empirical classification scheme based on the cumulative distribution function of the pulse energy as a function of observing frequency. We use this diagnostic to separate events with apparent spectral concentration from events with broader spectral coverage. Under this empirical classification scheme, most detected events show apparent spectral concentration within a limited frequency range. Events classified as apparently spectrally concentrated contain most of their measured relative energy within limited frequency ranges, whereas broadband events show more extended spectral coverage. We emphasize that this classification describes the observed spectral extent and should not by itself be interpreted as proof of intrinsically narrow-band emission. Spectral fitting shows that most apparently spectrally concentrated (ASC) GPs have negative spectral indices, while a few events exhibit positive slopes, indicating substantial spectral diversity within the sample. The 3$\sigma$ widths of ASC main pulse GPs appear to cluster around two characteristic ranges, although this feature should be interpreted with caution given the finite time resolution of the data. The energy distribution of ASC main pulse GPs is broadly consistent with a log-normal functional form at low-to-intermediate energies and resembles a power-law-like tail at the high-energy end. The waiting-time distribution can be described by a Weibull function, while a sliding-window comparison with Monte Carlo realizations of a Poisson distribution shows no statistically significant deviation from temporal independence over the present 18.9-min observing span. The CDF-based classification method developed here is transferable to other wideband receiver data, provided that careful consideration is given to the instrumental bandpass, frequency-dependent sensitivity, RFI masking, and signal-to-noise thresholds. These results provide observational constraints on the phenomenology of Crab GPs and may be useful for future studies of pulsar coherent emission and related radio transients. Full article

This study investigates the seismic ambient noise within the Campi Flegrei caldera (Naples, Italy) to improve the detection capability and reliability of the earthquake monitoring system managed by the INGV, Osservatorio Vesuviano. It focuses on the spectral characteristics and spatial variability of the ambient noise field, aiming to identify the dominant frequency bands that control signal detectability and to provide information for optimizing the monitoring network. Due to the dense urban environment surrounding the caldera, seismic recordings are often contaminated by anthropogenic noise, which can mask low-magnitude volcanic or seismic signals. Power spectral density (PSD) analysis was applied to evaluate background noise levels at several broadband stations from permanent and temporary seismic networks over the period January 2022 to January 2023. The resulting PSD estimates were compared with the global Peterson noise models to assess station performance. Results show marked variability among stations, related to local human activity, proximity to infrastructure, and different installation settings (buried vs. surface). The study emphasizes the importance of noise monitoring to ensure high-quality seismic data, support optimal station siting, and refine monitoring strategies in densely populated volcanic regions such as Campi Flegrei, where the reliable detection of low-amplitude seismic and volcanic signals is essential. Full article

This paper presents the design, calibration, and preliminary validation of a low-cost UAV–SDR system for spatial assessment of TETRA base station emissions. The proposed platform enables georeferenced electromagnetic field (EMF) measurements and 2D/3D mapping of signal distribution. The measurement results show good agreement with theoretical propagation models, confirming system reliability. In parallel, a fixed-site measurement campaign was conducted to analyze the temporal behavior of TETRA signals and their relation to broadband EMF levels. The results highlight distinct temporal patterns, with TETRA activity remaining stable or increasing during night-time, unlike the general EMF trend. This study demonstrates the feasibility of combining UAV-based and fixed-site approaches for comprehensive EMF assessment. Full article

Reservoir computing (RC) is a simple and highly efficient artificial neural network. For such a network, only the output connection weights need training, effectively reducing computational complexity. Optoelectronic time-delayed RC is typically based on an optoelectronic oscillator (OEO) with simultaneous broadband processing capabilities for both optical and electrical signals, while being readily implementable based on existing technologies. In this work, a new OEO-based RC (OEO-RC) using an electroabsorption modulated laser (EML) is designed, and the electroabsorption modulator (EAM) integrated in the EML serves as a nonlinear node. This scheme simplifies the architecture of an OEO-RC. And it is validated by using two typical tasks of the NARMA 10 time series prediction and the handwritten digit image recognition. Numerical results demonstrate that with optimized hyperparameters, this EML-based OEO-RC exhibits a comparable performance compared with some existing photonic time-delayed RCs. Full article

Bolted joints are critical load-transfer components in bridges, wind turbines, aerospace systems, mechanical equipment, and offshore platforms, where preload loss can degrade stiffness, accelerate fatigue, and compromise safety. For structural health monitoring, early monitoring of preload reduction before marked loosening is essential, yet existing ultrasonic guided wave indicators remain affected by frequency dependence, non-monotonic responses, amplitude drift, and environmental disturbances. This study proposes an early-warning-oriented preload identification method that combines broadband excitation, multi-frequency narrowband reconstruction, spectral centroid extraction, optimized weighted fusion, and fixed SC-domain linear calibration from one reference loading group. Using a 20–250 kHz Chirp response, 14 narrowband signals from 50 to 180 kHz were reconstructed for an M20 single-bolt specimen tested over 50–90 N·m. The fused spectral centroid index exhibited a stable, monotonic, and approximately linear relationship with preload. When fixed weights and calibration coefficients were transferred to held-out repeated-loading groups, all Pearson correlation coefficients exceeded 0.99. Feature-level robustness tests showed that the arithmetic mean of the spectral centroid reduced temperature-induced Range% by 98.42–99.08% and RSD by 98.89–99.31% relative to energy-based features. This work provides an interpretable multi-frequency spectral descriptor and a calibration transfer framework for repeatable early warning of preload loss in a controlled single-bolt configuration. Full article

This paper presents the design and experimental validation of a passive I/Q downconversion subsystem for X-band applications, with emphasis on maritime radar operation. The proposed architecture combines passive RF and LO distribution networks with a single-balanced passive mixer, enabling accurate quadrature signal generation without relying on active correction mechanisms. The subsystem maintains controlled amplitude and phase balance across the operating band, directly supporting effective image suppression. Experimental results demonstrate image rejection ratios exceeding 30 dB. The mixer stage exhibits a conversion loss of approximately 6 dB and an input-referred 1-dB compression point of about 14 dBm. The incorporation of an optimized RF matching stub in the mixer improves the impedance conditions at the IF node, leading to enhanced linearity and enabling a favorable trade-off between conversion loss and 1-dB compression point. Performance further improves within the maritime radar allocation, where enhanced balance leads to increased image rejection. These results confirm that high-quality I/Q signal generation can be achieved using a passive and low-complexity architecture, providing a practical and reliable solution for broadband X-band receiver front-ends. Full article