Search Results (260)

Tunable external cavity diode lasers (ECDLs) are core light sources for portable quantum precision measurement, offering narrow linewidth, wide tuning range, and high spectral purity. This review systematically summarizes the research progress of ECDLs for portable quantum applications, classifying mainstream configurations into Littrow, Littman, fiber grating, and filter types. The structural principles, performance characteristics, and recent breakthroughs of each type are elaborated, with in-depth analysis of the trade-offs among tuning range, linewidth, side-mode suppression ratio (SMSR), and output power. Key progress in miniaturization and integration is highlighted, focusing on MEMS-driven tuning and silicon waveguide hybrid integration technologies, which address the conflict between performance and portability. Current challenges including mode hopping, thermal stability, and packaging loss are discussed, and future directions such as multi-band extension, isolator-free frequency stabilization, and AI-assisted control are prospected. This work provides a systematic reference for the development of compact, high-performance ECDLs toward field-deployable quantum sensors. Full article

Lane keeping under degraded visual confidence remains challenging because most existing approaches focus either on improving lane-feature extraction or on estimating vehicle motion, while giving less attention to how unreliable visual measurements should modify the estimator–controller interaction in a physical closed-loop system. This paper presents a confidence-gated Kalman lane-keeping architecture for a 1:10-scale autonomous vehicle. The methodological contribution lies in the direct coupling of visual confidence, state estimation, and steering control: unreliable lane measurements are down-weighted through confidence-dependent measurement noise, while the propagated lane-relative state remains available to the controller. The primary experimental unit is the run, defined as one logged lap under one control configuration; frame-level summaries are retained only as historical reproducibility material. In the run-level comparison, the autonomous vision, inertial measurement unit (IMU)-feedforward, and Kalman filter (KF) group KF_G1—the first inferential KF generation—had lower mean absolute error than the human baseline, while vision and KF_G1 had overlapping run-level confidence intervals for absolute error. KF_G1 shifted the mean signed bias closer to the lane reference than the vision and IMU groups, but with higher run-level spread than vision. KF_G2, the second observational KF generation, is reported only as an observational generation comparison, so no causal claim is made for its estimator–controller correction weight $K_s=0.15$ setting. KF_G3, the single descriptive adverse-condition KF run, is reported without an estimable confidence interval or population-level adverse-illumination inference. A further limitation is that the inertial prediction pathway was inactive in the logged Kalman-filter runs because the inertial coupling coefficient $\alpha =0$. The main contribution is a reproducible run-level evaluation of confidence-gated estimator–controller coupling that distinguishes supported evidence from observational and descriptive cases. Full article

Intelligent transportation and aerial remote sensing scenes suffer from complex scene variations, abundant miniature targets and unpredictable out-of-distribution obstacles, which brings tough mathematical challenges to open-world detection tasks. Conventional detection algorithms lack rigorous frequency-domain separation and spatial constraint mathematical formulations, resulting in severe tiny-object feature attenuation, inefficient multimodal feature matching and catastrophic forgetting during incremental category iteration. To solve these mathematical bottlenecks, this paper constructs the TPCA-Net model built upon frequency decomposition and spatial dependency mathematical modelling. The entire framework consists of four fixed core modules: High-Frequency-Aware Multi-Scale Feature Enhancement (HSE), Reparameterized Adaptive Text–Visual Alignment (RTA), Double Wildcard Spatial Dependency Fusion (WSF), and Incremental Forgetting-Free Dual-Path Detection (DPD). From the mathematical perspective, the HSE module adopts discrete cosine transform-based filtering equations to split high-frequency object details from low-frequency background signals and establishes cross-attention spatial constraint formulas to make up for missing contextual information of small targets. The RTA module introduces low-rank decomposition mathematical optimization and reparameterized tensor fusion rules to realize domain-adaptive text embedding calibration and zero-cost cross-modal mapping at the inference stage. The WSF module constructs dual-wildcard self-supervised mathematical loss to finish unsupervised unknown-object identification and builds decoupled semantic–spatial fusion equations to improve the positioning precision of novel targets. The DPD module designs two sets of independent optimization objective functions and category-freezing incremental mathematical constraints to avoid conflicting parameter updates and eliminate forgetting defects in new-class expansion. Validated on COCO, DOTA and AI-TOD datasets, TPCA-Net achieves 56.0% AP on COCO, 79.30% mAP on DOTA, and 40.5% overall AP with 28.7% small-object AP on AI-TOD while delivering an inference throughput of 101.2 FPS on the Tesla T4 edge GPU. The proposed method outperforms existing mainstream open-world detection algorithms in tiny-object and rare-category recognition while maintaining efficient inference speed. Full article

The continuous miniaturization of semiconductor and lithium-ion battery manufacturing processes has intensified the demand for stringent particulate control in cleanrooms while simultaneously increasing the importance of energy efficiency. However, conventional melt-blown (MB) electret filters suffer from severe filtration efficiency degradation under ISO 29463 discharge conditions, whereas glass fiber filters exhibit an excessive pressure drop. To address this trade-off, in this study we propose an electret–nanofiber hybrid multilayer filter and establish a dual-efficiency model for its systematic optimization. The proposed model integrates the slip flow effect of nanofibers and incorporates a structural resistance factor (β = 0.125) derived from the ultrasonic bonding process. Experimental validation demonstrates that the model achieves high predictive accuracy (R² = 0.9995), and the optimized hybrid filter maintains > 98.1% filtration efficiency after ISO 29463-5:2022 discharge testing, markedly outperforming conventional MB filters (41.4%). Furthermore, the hybrid filter exhibits a quality factor (QF) of 0.117, more than twice that of commercial glass fiber filters. These findings demonstrate that the proposed model-based framework provides robust design guidelines for next-generation energy-efficient air filtration systems capable of meeting stringent international standards. Full article

To address the stringent requirements for miniaturization and high reliability in the perception systems of mobile robotic platforms, this article presents an ultra-compact bandpass filter based on air core recta-coax lines using micro-electro-mechanical systems technology. The proposed filter features an air-filled cavity structure with internal coupled lines and a fully enclosed metal shield, which effectively minimizes dielectric and radiation losses while achieving a highly compact footprint. This compactness is particularly critical for robotic radar front-ends, where limited payload capacity demands high integration density. By leveraging classical filter synthesis theory, the design achieves a high-order response within a minimized volume. Furthermore, the inherent high-Q characteristic of the air cavity significantly improves out-of-band rejection, thereby effectively suppressing interference in complex electromagnetic environments and enhancing the signal-to-noise ratio for robotic detection. A prototype operating at 75 GHz was fabricated and measured. The experimental results demonstrate a low insertion loss of 1.5 dB and a compact size of 0.875 mm³, showing reasonable agreement with simulations. The proposed design offers a promising solution for next-generation, high-performance sensing units in autonomous robotics. Full article

The contribution of this paper is to propose the design and experimental validation of split-type dual- and tri-band bandpass filters (BPFs) based on highly miniaturized substrate-integrated coaxial cavities (SICCs). The proposed split-type multiband filter design achieves exceptional circuit-area efficiency within the SIW-related (substrate-integrated waveguide) split-type filter category. The size-reduced SICCs are fabricated using two substrates of different thicknesses. The coupling matrix method is employed to synthesize the responses of the example dual- and tri-band filters. The proposed dual-band filter achieves a circuit size of 0.17 λ_d × 0.17 λ_d, with insertion losses of 0.78 and 0.89 dB for the two passbands, and isolation between the passbands exceeding 15 dB. For the tri-band filter, the circuit size is 0.27 λ_d × 0.34 λ_d, with the insertion losses of 0.96, 2.6, and 1.21 dB across the three passbands, accompanied by similarly effective isolation. Experimental results validate the circuit designs and performance, demonstrating strong agreement between measured and simulated data. Full article

The passive nature of gravity matching navigation, along with its concealment and freedom from error accumulation over time, is essential for reducing inertial navigation system (INS) errors and enabling high-precision autonomous underwater positioning. The current paper provides a systematic review of major technologies in the field, including the development of underwater gravimeters, construction of gravity reference maps, suitable area selection, optimization of matching algorithms, gravity–inertial integrated navigation, and path planning. We discuss hardware developments, including classical sensors, gradiometers, and quantum sensors, as well as methodological concepts such as multi-source sensor data fusion, intelligent area selection, algorithm optimizations, connections between multiple filters, and intelligent trajectory design. Despite a relatively well-developed technical infrastructure, several bottlenecks remain, including the low engineering maturity of high-end hardware, poor algorithmic performance under extreme conditions, over-reliance on simulation, and weak module integration. Future research should focus on hardware miniaturization, cross-domain intelligent adaptive algorithms, multi-condition real-world validation, and the transition from loosely coupled to tightly coupled architectures to achieve improved accuracy and robustness. Full article

This paper presents a miniaturized ultra-wideband high-pass filter integrated with a notch function based on low-temperature co-fired ceramic (LTCC). The design motivation is to realize continuous wideband high-pass transmission while rejecting a narrow in-band interference/leakage component in compact RF front-end modules. The proposed design employs a cascaded structure of a seventh-order quasi-elliptic HPF and a three-section $\lambda /4$ stub notch filter in a single multilayer LTCC chip. Multiple transmission zeros (TZs) are introduced to improve the lower-stopband selectivity, while the three-section coupled-line NF produces a tunable localized rejection band. The LTCC implementation further integrates multilayer capacitors, three-dimensional helical inductors, shielded strip-line coupling stubs, a grounding compensation capacitor, and an isolation wall to balance compactness, impedance matching, and parasitic suppression. The fabricated chip achieves an ultra-wide bandwidth of 2.35 octaves, a notch 20 dB FBW of 8.5%, an insertion loss below 2 dB, a 60 dB roll-off rate of 154.1 dB/GHz within the lower stopband, and a voltage standing wave ratio (VSWR) less than 2. Experimental results validate that the proposed compact chip meets communication requirements and is suitable for 5G base stations, radar systems, and other applications. The chip dimensions are 4.5 mm × 3.2 mm × 2.5 mm. Full article

To address the structural complexity, limited detection sensitivity, and environmental susceptibility of the stable operating point in conventional fiber-optic current transformers for low-current detection, this study proposes a fiber-optic current transformer based on the coupling of an extrinsic Fabry–Perot interferometer (EFPI) and a lead zirconate titanate piezoelectric ceramic (PZT). In the proposed sensor, a toroidal magnetic core and an induction winding are used as the current pickup unit to convert the measured alternating current into an induced voltage. This induced voltage directly drives the PZT to generate axial displacement, causing periodic variations in the length of the air Fabry–Perot cavity formed between the fiber end face and the coated quartz diaphragm. As a result, the current signal is converted into an optical interference intensity signal. To prevent the static operating point from deviating from the optimal linear region during EFPI intensity demodulation, a DC-component-feedback-based operating point control method is proposed. By adjusting the driving voltage of the fiber Fabry–Perot tunable filter, the center wavelength of the incident narrowband demodulation light can track the optimal operating point of the interference spectrum, thereby improving the stability of the intensity demodulation process. Experimental results show that the fabricated sensor can generate a stable reflected interference spectrum and exhibits a relatively flat frequency response within the range of 0–7 kHz, indicating its potential for power-frequency current detection under the present laboratory conditions. When the measured current is 0.13 mA, the sensor can still produce a distinguishable sinusoidal output signal. When the measured current increases to 75 mA, obvious nonlinear distortion appears in the output signal, indicating that the sensor is approaching the boundary of its linear detection range. Within the linear operating region, the output peak-to-peak value shows good linearity with the measured current. The results indicate that the proposed EFPI-PZT fiber-optic current transformer has the advantages of a relatively simple structure, clear low-current response, and adjustable structural parameters, providing a reference for the miniaturized design and further development of new fiber-optic current sensors. Full article

With the rapid expansion of 5G millimeter-wave communications, there is a strong demand for compact, low-loss, and high-selectivity filtering components. This paper presents the design and analysis of a compact dual-band substrate integrated waveguide (SIW) bandpass filter operating at 28 GHz and 38 GHz for 5G applications. The proposed structure employs shunt iris-loaded resonators integrated within the SIW cavity to achieve dual-band operation with improved frequency selectivity. The designed filter provides a narrow passband of 1.2 GHz at 28 GHz and a wider passband of 2.6 GHz at 38 GHz, while maintaining a compact footprint of 8.5 mm × 6.2 mm. It is implemented on a Rogers RT/Duroid 5880 substrate (${\epsilon }_r$ = 2.2, h = 0.508 mm), ensuring low dielectric loss and stable high-frequency performance. The simulated results demonstrate excellent return loss of 44.2 dB at 28.1 GHz and 52.7 dB at 38.3 GHz, along with a low insertion loss of approximately 0.68 dB, confirming efficient signal transmission. Furthermore, the design is validated using a simulation with ADS of second-order Butterworth equivalent circuit, providing design simplicity and demonstrating the feasibility of practical fabrication. On the other hand, it is well suited for integration into compact 5G front-end modules requiring high performance, miniaturization, and dual-band operation. Full article

Existing ground-slotted coplanar waveguide (CPW) spoof surface plasmon polariton (SSPP) low-pass filters (LPFs) remain constrained by the difficulty of achieving a wide stopband while maintaining a compact size, as well as by undesired radiation leakage arising from their open-aperture slot configuration. To address these issues, a grounded coplanar waveguide spoof surface plasmon polariton (GCPW-SSPP) low-pass filter based on a multi-arm star-shaped slot (MASS) loading topology is proposed. An equivalent-circuit interpretation and full-wave dispersion analysis show that the multi-arm slots introduce enhanced distributed reactive loading, thereby lowering the asymptotic frequency and enabling compact SSPP implementations. The near-field characteristics further demonstrate tighter electromagnetic confinement, as reflected by an approximately 48% reduction in the electric-field confinement width along the z-direction. To alleviate the trade-off between miniaturization and wide-stopband performance in cascaded SSPP LPFs, the single-cell S-parameters of the proposed topology are investigated. A single MASS unit exhibits a sharp cutoff and a deep transmission notch, allowing a wide stopband to be obtained with fewer cascaded cells. Radiation characteristics are subsequently quantified by a loss-decomposition method, and the MASS topology is found to suppress the radiation leakage of open-aperture ground-slotted structures, yielding a maximum radiation-loss reduction of approximately 75%. To validate the design methodology, a MASS-loaded GCPW-SSPP LPF is designed, fabricated, and measured. The measured results are in good agreement with the simulated ones, confirming the effectiveness of the proposed scheme. By simultaneously achieving a wide stopband, compact size, and suppressed radiation leakage, the proposed filter offers a promising low-interference filtering solution for highly integrated microwave and RF front-end systems. Full article

Amplified Spontaneous Emission (ASE) sources are widely employed as highly stable broadband sources in fields such as high-precision navigation and optical detection. Erbium-doped fiber (EDF), as the core active component in ASE sources, has long been a key subject of thermal stability research. We fabricated a low-doped EDF with an 80 μm-cladding using the vapor phase doping (VPD) technique. This EDF was compared with a commercial 125 μm-cladding EDF using a double-pass forward (DPF) optical path configuration with a narrowband filter. We investigated the temperature-dependent characteristics of the ASE spectra generated by the two EDFs with different parameters. The temperature drift performance of the two EDFs was analyzed based on three critical indicators of the spectrum: mean wavelength, spectral bandwidth, and output power. In comparison with the commonly used EDF, the results show that a properly designed small-cladding EDF with an appropriate length can deliver higher ASE output power and exhibit a lower mean-wavelength temperature drift. This study provides an important guideline for promoting the miniaturization of high-precision fiber-optic sensing devices. Full article

In the fields of atomic physics, quantum sensing, and precision measurement, 852 nm lasers are essential for the resonant excitation and manipulation of the cesium (Cs) D₂ transition ($6S_{1/2}\to 6P_{3/2}$). While significant global progress has been made in developing 852 nm laser based on distributed feedback (DFB) lasers and external cavity diode lasers (ECDL), the burgeoning demand for portable and integrated quantum instruments imposes stringent requirements on miniaturization and long-term, maintenance-free operation. To address the challenge of mode competition in Faraday lasers, this work demonstrates a frequency-stabilized semiconductor laser based on an atomic frequency-selective architecture. By utilizing a customized Faraday Anomalous Dispersion Optical Filter (FADOF) for frequency selection, the laser wavelength automatically corresponds to the Cs 852 nm D₂ transition, offering “Plug-and-play” operation. To further enhance integration, we propose and demonstrate a miniaturized Faraday laser architecture that resolves the instability caused by the mismatch between the FADOF transmission bandwidth and the free spectral range (FSR) of the external cavity. By employing a 7000 Gs magnetic field, the FADOF bandwidth is actively broadened to ∼15 GHz, while the cavity length is concurrently compressed to 30 mm to maximize FSR to effectively suppressing unstable mode competition. The resulting laser achieves a highly compact dimension of $102\times 109\times 96{\mathrm{mm}}^3$. Performance testing demonstrates a Lorentzian fitted linewidth of $16.4\mathrm{kHz}$ and a 1-s frequency stability of $3.05\times {10}^{-13}$ after modulation transfer spectroscopy (MTS)-based frequency locking. This robust and autonomous 852 nm laser source provides a critical technological foundation for the miniaturization of high-performance quantum sensors. Full article

Hyperspectral sensing allows for the capture of spatially resolved spectral data, a capability critical for applications spanning from remote sensing to biomedical diagnostics. Nevertheless, the widespread adoption of this technology is hindered by the bulk and complexity of traditional systems based on diffractive optics. To overcome these hurdles, substantial research efforts have been dedicated to system miniaturization via component scaling and computational imaging. This review outlines the technological progression of compact hyperspectral imaging, ranging from miniaturized dispersive elements and tunable filters to computational snapshot designs using optical multiplexing. Although these approaches decrease system volume, they generally treat the sensor as a passive intensity recorder requiring external encoding. Therefore, we focus here on the rising paradigm of sensor-level integration made possible by nanomanufacturing. We examine optics-free architectures where spectral discrimination is embedded directly into the pixel, distinguishing between pixel-level nanophotonic filtering and intrinsic material-based selectivity. We specifically highlight emerging platforms such as compositionally engineered and cavity-enhanced perovskites, as well as electrically tunable organic or two-dimensional (2D) material heterostructures. To conclude, this review discusses persistent challenges regarding fabrication uniformity and stability, providing an outlook on the future of scalable and fully integrated hyperspectral vision systems. Full article

While direct current (DC) ice-melting is currently adopted for some transmission lines, its application to 10 kV distribution transformers—often located in remote and rugged terrain—presents significant operational challenges. Disconnecting these transformers prior to ice-melting is a complex procedure that incurs substantial labor, material, and financial costs. Leaving transformers connected risks DC current flowing into idle windings, potentially causing damage. Furthermore, existing mobile DC ice-melting power supplies are bulky and impose stringent transportation requirements, rendering them unsuitable for use on mountain roads. To overcome these limitations, this paper proposes a compact, lightweight variable-frequency ice-melting device. The operating principle and output characteristics of the variable-frequency method are investigated in detail. Using Simulink, system modeling and simulation analyses are performed to obtain the voltage and current output characteristics, along with harmonic spectra. Simulation results demonstrate that the proposed device achieves significant miniaturization compared with conventional solutions: within the typical parameter range of conventional devices, the volume can be reduced by 44–58% and the weight by 43–52%. In addition, the selected LC filter parameters (L = 10.39 mH, C = 86.62 μF) represent an optimized compromise solution that effectively suppresses input harmonics while maintaining the output current total harmonic distortion (THD) within an acceptable limit of 3.6%. Experimental results further validate the feasibility of the variable-frequency ice-melting current. Based on a matrix converter topology, the proposed device enables flexible adjustment of the output melting voltage and frequency, exhibits excellent low-frequency performance and dynamic response, and maintains low output harmonic content—fully meeting the application requirements for variable-frequency ice-melting. The key novelty lies in a compact matrix-converter-based de-icing device with systematic low-frequency performance analysis, offering superior portability and adaptability over traditional DC solutions. Full article