Ultra-wideband Research Articles

UVIO: Adaptive Kalman Filtering UWB-Aided Visual-Inertial SLAM System for Complex Indoor Environments

Precise positioning in an indoor environment is a challenging task because it is difficult to receive a strong and reliable global positioning system (GPS) signal. For existing wireless indoor positioning methods, ultra-wideband (UWB) has become more popular because of its low energy consumption and high interference immunity. Nevertheless, factors such as indoor non-line-of-sight (NLOS) obstructions can still lead to large errors or fluctuations in the measurement data. In this paper, we propose a fusion method based on ultra-wideband (UWB), inertial measurement unit (IMU), and visual simultaneous localization and mapping (V-SLAM) to achieve high accuracy and robustness in tracking a mobile robot in a complex indoor environment. Specifically, we first focus on the identification and correction between line-of-sight (LOS) and non-line-of-sight (NLOS) UWB signals. The distance evaluated from UWB is first processed by an adaptive Kalman filter with IMU signals for pose estimation, where a new noise covariance matrix using the received signal strength indicator (RSSI) and estimation of precision (EOP) is proposed to reduce the effect due to NLOS. After that, the corrected UWB estimation is tightly integrated with IMU and visual SLAM through factor graph optimization (FGO) to further refine the pose estimation. The experimental results show that, compared with single or dual positioning systems, the proposed fusion method provides significant improvements in positioning accuracy in a complex indoor environment.

Miniaturised ultra‐wideband circular polarised koch fractal crossed dipole array

AbstractUltra‐wideband (UWB) systems utilise a broad frequency spectrum to achieve high data transmission rates and enhanced precision, creating a demand for specialised UWB antennas. Circularly Polarised (CP) antennas are considered essential for maintaining robust performance under varied environmental conditions. Among them, the crossed dipole is effective for UWB CP applications, but its relatively large size could limit its use in various systems. A miniaturised crossed dipole design employing the Koch fractal structure is proposed and the measurement results are presented. The prototype antenna achieved an effective bandwidth covering 88% of the frequency range from 1.4 to 3.6 GHz. Additionally, a 4 × 4 array using this design was tested in the same frequency band, demonstrating beam‐steering capabilities up to 30°. The proposed antenna has demonstrated effective deployment in diverse communication systems and phased array applications within ultra‐wideband (UWB) CP environments.

A novel UWB in‐body printed microstrip feed monopole antenna with dual band‐stop capabilities

AbstractThis paper presents an innovative and condensed blueprint for an ultra‐wideband (UWB) printed monopole antenna, aiming to augment bandwidth and achieve dual band‐stop capabilities, all while accounting for the impact of the human body model on stop bands. The proposed design showcases a square radiating patch situated on the top layer of the substrate, complemented by a ground plane etched on the underside, integrating two sets of adapted U‐shaped slots. Such a configuration delivers a broad operational fractional bandwidth that surpasses 132%. Within our design, a modified C‐shaped slot in the radiation patch creates the first band‐stop property, while a pair of modified F‐shaped slots etched in the radiation patch generates the second stop‐band property. Measuring 12 mm × 18 mm × 0.8 mm, the antenna offers a compact form factor, broad bandwidth, cost‐effectiveness, omnidirectional radiation patterns within the H‐plane and acceptable behavior for using in In‐body microwave applications.

Theoretical design and implementation of equal and unequal split ultra-wide band Wilkinson power divider with Chebyshev impedance transform

Abstract In this study, we designed multi-section UWB Wilkinson power dividers for both equal and unequal power divider. The key innovation is successfully matching these power dividers using the Chebyshev method. The proposed method achieves very low insertion losses and high transmission coefficients across the ports. For the three-section equal power divider, Chebyshev polynomials were used to model the reflection coefficient, and the characteristic impedance for each section was calculated symmetrically. The design achieved a fractional bandwidth of 106% for a 20 dB return loss, with an insertion loss of 0.3 dB. For unequal multi-section dividers, power division ratios of 1.5:1 and 2:1 were chosen. Theoretical microwave calculations were used to determine the input and output transmission line impedances. Chebyshev approximation was then applied to design the three-section unequal power dividers. The return losses for these unequal dividers were measured at 17 dB and 15 dB, with fractional bandwidths of 120% and 126%. Both circuits had insertion losses of 0.25 dB. The consistent results from analytical calculations, simulations, and measurements confirm the effectiveness of the Chebyshev method for both equal and unequal power division.

An Ultra-wideband Metamaterial Absorber with Angular Stability

In this paper, an ultra-wideband (UWB) microwave absorber with robust angular stability is proposed. Each unit of the structure consists of three-layer stacked resistive films to effectively broaden the absorption bandwidth. A metallic via is inserted in the center of the structure, which effectively guides the TM polarization oblique incident wave power to propagate vertically and be absorbed by the resistive films, thus enhancing the angular stability of TM polarization. Within the frequency range of 3.2 GHz to 35.5 GHz, the absorptivity surpasses 90% and the fractional bandwidth reaches 167%. Within an incident angle range of 0∘ to 60∘, the absorptivity of TE polarization remains at about 80%, and the TM polarization can be maintained at over 90%. The absorption mechanism was analyzed by surface power loss and surface current distribution. A sample was fabricated, and the measured results are consistent with the simulated ones. The absorber displays good angular stability and broad bandwidth, making it ideal for electromagnetic stealth applications.

RLI-SLAM: Fast Robust Ranging-LiDAR-Inertial Tightly-Coupled Localization and Mapping.

Simultaneous localization and mapping (SLAM) is an essential component for smart robot operations in unknown confined spaces such as indoors, tunnels and underground. This paper proposes a novel tightly-coupled ranging-LiDAR-inertial simultaneous localization and mapping framework, namely RLI-SLAM, which is designed to be high-accuracy, fast and robust in the long-term fast-motion scenario, and features two key innovations. The first one is tightly fusing the ultra-wideband (UWB) ranging and the inertial sensor to prevent the initial bias and long-term drift of the inertial sensor so that the point cloud distortion of the fast-moving LiDAR can be effectively compensated in real-time. This enables high-accuracy and robust state estimation in the long-term fast-motion scenario, even with a single ranging measurement. The second one is deploying an efficient loop closure detection module by using an incremental smoothing factor graph approach, which seamlessly integrates into the RLI-SLAM system, and enables high-precision mapping in a challenging environment. Extensive benchmark comparisons validate the superior accuracy of the proposed new state estimation and mapping framework over other state-of-the-art systems at a low computational complexity, even with a single ranging measurement and/or in a challenging environment.

Multifunctional electromagnetic wave absorbing carbon fiber/Ti3C2TX MXene fabric with ultra-wide absorption band

In order to provide electronics and aerospace equipment with effective immunity to electromagnetic interference and to improve their adaptability to very harsh electromagnetic environments, high-performance electromagnetic wave-absorbing materials are urgently needed for civil and military applications. Unfortunately, their effective absorption bandwidth width is still unsatisfactory (<10 GHz) due to the insufficient regulation of their component mixing and microstructure. By employing nanocage-structured UiO-66 as a doping phase, MXene/ZrO2/tungsten-doped carbon (MXene/ZrO2/W-C) interpenetrating fiber networks were prepared by the electrostatic spinning method. According to the experimental results, the introduction of the dopant phase and the formation of the interpenetrating network significantly improves impedance matching, resulting in a wide absorption bandwidth of 11.12 GHz for the composites, completing the coverage of the X and Ku bands. The radar scattering cross section of MXene/ZrO2/W-C has been simulated using three-dimensional electromagnetic field simulation, and as a result of its excellent stealth performance, it is able to generate corresponding electromagnetic responses in radar detection environments that exhibit different far-field emission bands. Further, MXene/ZrO2/W-C exhibits outstanding hydrophobicity, corrosion resistance, and temperature resistance. These characteristics allow it to be used for the preparation of electromagnetic wave (EMW) absorbing devices for complex environmental applications. It is important to note that the results of this study will be extremely useful in the development of composites based on MXene with ultra-wide absorption bands as well as in the analysis of EMW absorption mechanisms.

Radar Based Secure Contactless Fall Detection Using Hybrid Optimizer with Convolution Neural Network

Introduction: senior citizens can lead to severe injuries. Existing wearable fall-alert sensors are often ineffective as seniors tend to avoid using them, highlighting the need for non-contact sensor applications in smart homes. This study proposes a CNN-based fall detection system using time-frequency analyses. A unique hybrid optimizer, GWO-ABC, combining Artificial Bee Colony (ABC) and Grey Wolf Optimizer (GWO), is employed to optimize CNN architectures. Radar return signals are transformed into spectrograms and binary images for training the HOCNN with fall and non-fall data.Methods: Radar signals are processed using short-time Fourier transformation to create time-frequency spectrograms, converted into binary images. These images are fed into a CNN optimized by the GWO-ABC algorithm. The CNN is trained on labelled fall and non-fall instances, focusing on high-level feature extraction.Results: The HOCNN showed superior accuracy in fall detection, successfully extracting critical high-level features from radar signals. Performance metrics, including precision, recall, and F1-score, demonstrated significant improvements over traditional methods.Conclusion: This study introduces a non-contact, automatic fall detection system for smart homes using GWO-ABC optimized CNNs, offering a promising solution for enhancing geriatric care and ensuring senior citizen safety. Index Terms—Grey Wolf Optimizer, Artificial Bee Colony algorithm, Convolutional neural network, fall detection, time-frequency analysis, ultra-wideband (UWB) radar

Ultra‐Wideband Terahertz Integrated Polarization Multiplexer

AbstractPolarization‐division multiplexing is crucial for increasing channel capacity and spectral efficiency in communications. A key component is the polarization multiplexer, which combines or separates signals with orthogonal polarizations. Existing planar multiplexers lack an ultrawide band for terahertz communications. While microwave‐inspired orthomode transducers (OMTs) provide broadband operation, they suffer from high ohmic loss and bulkiness at terahertz frequencies. Optical integrated polarization beam splitters (PBSs) offer low loss and good integrability but have narrow bandwidths. This work presents a substrateless all‐silicon polarization multiplexer based on tapered directional couplers and air‐silicon effective mediums, integrated monolithically on a compact footprint. The device demonstrates a 37.8% fractional bandwidth, an average insertion loss of 1 dB, and a polarization extinction ratio above 20 dB over 225–330 GHz. This superior performance is enabled by the anisotropy of the effective medium claddings, affecting the two orthogonal guided modes differently. The multiplexer enables simultaneous two‐channel terahertz fiber communications with polarization diversity. It supports aggregated data rates up to 155 and 190 Gbit with bit error rates below hard‐ and soft‐decision forward‐error‐correction limits, respectively. This advancement holds promise for 6G terahertz integrated systems with enhanced channel capacities.

1D-CLANet: A Novel Network for NLoS Classification in UWB Indoor Positioning System

Ultra-Wideband (UWB) technology is crucial for indoor localization systems due to its high accuracy and robustness in multipath environments. However, Non-Line-of-Sight (NLoS) conditions can cause UWB signal distortion, significantly reducing positioning accuracy. Thus, distinguishing between NLoS and LoS scenarios and mitigating positioning errors is crucial for enhancing UWB system performance. This research proposes a novel 1D-ConvLSTM-Attention network (1D-CLANet) for extracting UWB temporal channel impulse response (CIR) features and identifying NLoS scenarios. The model combines the convolutional neural network (CNN) and Long Short-Term memory (LSTM) architectures to extract temporal CIR features and introduces the Squeeze-and-Excitation (SE) attention mechanism to enhance critical features. Integrating SE attention with LSTM outputs boosts the model’s ability to differentiate between various NLoS categories. Experimental results show that the proposed 1D-CLANet with SE attention achieves superior performance in differentiating multiple NLoS scenarios with limited computational resources, attaining an accuracy of 95.58%. It outperforms other attention mechanisms and the version of 1D-CLANet without attention. Compared to advanced methods, the SE-enhanced 1D-CLANet significantly improves the ability to distinguish between LoS and similar NLoS scenarios, such as human obstructions, enhancing overall recognition accuracy in complex environments.

INS/UWB fusion localization algorithm in indoor environment based on variational Bayesian and error compensation

Localization technology is crucial for indoor robot navigation. However, because of the intricacies inherent in the indoor setting, the signal transmission is vulnerable to the interference of obstacles, which leads to the decline of positioning accuracy. Ultra-Wideband (UWB) has the characteristics of channel insensitivity and high localization accuracy. Inertial navigation system (INS) functions independently as a navigation system, and its positioning results will not be affected due to non-line-of-sight (NLOS) interference. When using UWB to locate the mobile node, the Variational Bayesian Gaussian Mixture Model (VBGMM) clustering algorithm based on Gaussian Mixture Model (GMM) is applied to lessen the influence of NLOS propagation. This paper proposed a loose coupling of the INS and UWB, which combines the advantages of the two subsystems and improves the performance of the positioning system. On the basis of INS autonomous positioning, the maximum entropy fuzzy generalized probability data association filter (MEF-GPDAF) is used to modify the INS positioning results, and then the virtual inertia points are further built to compensate the error of the corrected coordinates. Finally, Unscented Kalman Filter is applied to the compensated coordinates for enhanced positioning. Simulation indicates that the proposed approach in this paper exhibits superior location accuracy. The real experimental results show that the proposed algorithm achieves an average improvement of 61.12% in positioning accuracy.

Dual-Mode Embedded Impulse-Radio Ultra-Wideband Radar System for Biomedical Applications.

This paper presents a real-time and non-contact dual-mode embedded impulse-radio (IR) ultra-wideband (UWB) radar system designed for microwave imaging and vital sign applications. The system is fully customized and composed of three main components, an RF front-end transmission block, an analog signal processing (ASP) block, and a digital processing block, which are integrated in an embedded system. The ASP block enables dual-path receiving for image construction and vital sign detection, while the digital part deals with the inverse scattering and direct current (DC) offset issues. The self-calibration technique is also incorporated into the algorithm to adjust the DC level of each antenna for DC offset compensation. The experimental results demonstrate that the IR-UWB radar, based on the proposed algorithm, successfully detected the 2D image profile of the object as confirmed by numerical derivation. In addition, the radar can wirelessly monitor vital sign behavior such as respiration and heartbeat information.

FAST Detection of OH Emission in the Carbon-rich Planetary Nebula NGC 7027

We present the first detection of the ground-state OH emission line at 1612 MHz toward the prototypical carbon-rich planetary nebula (PN) NGC 7027, utilizing the newly installed ultrawideband (UWB) receiver of the Five-hundred-meter Aperture Spherical radio Telescope (FAST). This emission is likely to originate from the interface of the neutral shell and the ionized region. The other three ground-state OH lines at 1665, 1667, and 1721 MHz are observed in absorption and have velocities well matched with that of HCO+ absorption. We infer that the OH absorption is from the outer shell of NGC 7027, although the possibility that they are associated with a foreground cloud cannot be completely ruled out. All the OH lines exhibit a single blueshifted component with respect to the central star. The formation of OH in carbon-rich environments might be via photodissociation-induced chemical processes. Our observations offer significant constraints for chemical simulations, and they underscore the potent capability of the UWB receiver of FAST to search for nascent PNe.

Improvement of SAW Resonator Performance by Petal-like Topological Insulator.

This article introduces a novel petal-like SAW topology insulator, which can transmit sound waves with low loss and high flexibility in an ultra-wide frequency band by simultaneously adjusting multiple structural parameters of phononic crystals. Using finite element analysis, it was found that adjusting these parameters can generate a broadband gap of 55.8-65.7 MHz. This structure can also achieve defect immunity and sharp bending in waveguide transmission. When this topology insulator is applied to resonators, compared to traditional designs, the insertion loss is reduced by 22 dB, the on-load quality factor is increased by 227%, the off-load quality factor is increased by 1024.5%, and the quality sensitivity is improved by 3.7 times compared to bare devices.

UWB/MEMS IMU integrated positioning method based on NLOS angle discrimination and MAP constraints

A dynamic nonline-of-sight (NLOS) angle discrimination method is proposed to address the insufficiency of current research on the NLOS error characteristics of ultrawideband (UWB) signals in dynamic environments as well as the problem that UWB signals frequently suffer from occlusion, leading to poor or impossible localization. The experimental results indicate that the degree of UWB signal occlusion increases as the horizontal angle decreases, and when the horizontal angle is less than 167°, the UWB ranging error is so large that no ranging value is available. On this basis, a tightly integrated UWB/MEMS IMU positioning algorithm incorporating NLOS angle discrimination and map constraints is proposed; it employs horizontal angles to discriminate UWB ranging values in NLOS environments in accordance with the dynamic NLOS characteristics of UWB signals to assign better weights to UWB observations. Through comparative analysis of the results from both groups of experiments, the algorithm achieved northward, eastward, and planar positioning errors of 0.189 m and 0.126 m, 0.119 m and 0.134 m, 0.243 m and 0.211 m, respectively. Compared to the Robust Adaptive Kalman Filtering algorithm, the positional accuracy in the plane improved by 22.9% and 28.5%, respectively.

Deep neural network-enabled multifunctional switchable terahertz metamaterial devices

Under the support of deep neural networks (DNN), a multifunctional switchable terahertz metamaterial (THz MMs) device is designed and optimized. This device not only achieves ideal ultra-wideband (UWB) absorption in the THz frequency range but enables dual-functional polarization transformation over UWB. When vanadium dioxide (VO2) is in the metallic state, the device as a UWB absorber with an absorption rate exceeding 90% in the 2.43–10 THz range, with a relative bandwidth (RBW) of 145.2%, and its wideband absorption performance is insensitive to polarization. When VO2 is in the insulating state, the device can switch to a polarization converter, achieving conversions from linear to cross polarization and from linear to circular polarization in the ranges of 4.58–10 THz and 4.16–4.43 THz, respectively. Within the 4.58–10 THz range, the polarization conversion ratio approaches 100% with an RBW of 74.3%, the polarization rotation angle is near 90°. Within the 4.16–4.43 THz range, the RBW is 6.29% and the ellipticity ratio approaches 1, Moreover, the effects of incident angle and polarization angle on the operational characteristics are studied. This THz MMs due to its advantages of wide angle, broad bandwidth, and high efficiency, provides valuable references for the research of new multifunctional THz devices. It has great application potential in short-range wireless THz communication, ultrafast optical switches, high-temperature resistant switches, transient spectroscopy, and optical polarization control devices.

Therapeutic Exercise Recognition Using a Single UWB Radar with AI-Driven Feature Fusion and ML Techniques in a Real Environment.

Physiotherapy plays a crucial role in the rehabilitation of damaged or defective organs due to injuries or illnesses, often requiring long-term supervision by a physiotherapist in clinical settings or at home. AI-based support systems have been developed to enhance the precision and effectiveness of physiotherapy, particularly during the COVID-19 pandemic. These systems, which include game-based or tele-rehabilitation monitoring using camera-based optical systems like Vicon and Microsoft Kinect, face challenges such as privacy concerns, occlusion, and sensitivity to environmental light. Non-optical sensor alternatives, such as Inertial Movement Units (IMUs), Wi-Fi, ultrasound sensors, and ultrawide band (UWB) radar, have emerged to address these issues. Although IMUs are portable and cost-effective, they suffer from disadvantages like drift over time, limited range, and susceptibility to magnetic interference. In this study, a single UWB radar was utilized to recognize five therapeutic exercises related to the upper limb, performed by 34 male volunteers in a real environment. A novel feature fusion approach was developed to extract distinguishing features for these exercises. Various machine learning methods were applied, with the EnsembleRRGraBoost ensemble method achieving the highest recognition accuracy of 99.45%. The performance of the EnsembleRRGraBoost model was further validated using five-fold cross-validation, maintaining its high accuracy.

Ultra-wideband bandpass microstrip filter with electronically tunable notch-band

This paper introduces a compact ultra-wideband (UWB) microstrip filter featuring both a fixed and an electronically tunable notch band. Operating within the frequency range of 3.27 GHz to 5.61 GHz, the filter incorporates a permanent notch at 4.08 GHz and a tunable notch at 4.88 GHz. Utilizing a traditional ground plane and a short-circuited transmission line, we develop a bandpass filter with a stable notch-band positioned and another tunable notch band. Systematic defects are made to the ground plane to increase the coupling between input and output ports leading to UWB response. The stable notch band is created using a rectangular slot resonator, while the tunable notch employs a varactor diode (NXP BB135 Varactor Diode) integrated into a rectangular stub. Operating in the even-mode with symmetrical current distribution, the filter exhibits a -3dB passband bandwidth of 740 MHz, 610 MHz, and 240 MHz across its respective passbands. Notch band attenuation measures at -10 dB and -9 dB, respectively. Experimental results from the prototype demonstrate excellent agreement with simulated results, confirming the efficacy of the design.

Hypnos: A Contactless Sleep Stage Monitoring System Using UWB Signals

As a fundamental physiological process, sleep plays a vital role in human health. High-quality sleep requires a reasonable distribution of sleep duration over different sleep stages. Recently, contactless solutions have been used for in-home sleep stage monitoring via wireless signals as it enables monitoring daily sleep in a non-intrusive manner. However, various factors, such as the subject's physiological characteristics during sleep, the subject's health status, and even the sleep environment, pose challenges to wireless signal analysis. In this paper, we propose Hypnos, a contactless sleep monitoring system that identifies different sleep stages using an ultra-wideband (UWB) device. Hypnos enables automated bed localization and extracts signals containing coarse-grained body movements and fine-grained chest movements due to breathing and heartbeat from the subject, which acts as the preparation step for sleep staging. The key to our system is a seq2seq deep learning model, which adopts an attention-based sequence encoder to learn the patterns and transitions within and between sleep epochs and combines with contrastive learning to improve the generalizability of the encoder. Particularly, we incorporate sleep apnea detection as an auxiliary task into the model to reduce the interference of sleep apnea with sleep staging. Moreover, we design a two-step training for better adaptation of subjects with different severities of sleep disorders. We conduct extensive experiments on 100 subjects, including healthy individuals and patients with sleep disorders, and the experimental results show that Hypnos achieves excellent performance in multi-stage sleep classification (including 5-stage sleep classification), and outperforms other baseline methods.

ReLoki: A Light-Weight Relative Localization System Based on UWB Antenna Arrays.

Ultra Wide-Band (UWB) sensing has gained popularity in relative localization applications. Many localization solutions rely on using Time of Flight (ToF) sensing based on a beacon-tag system, which requires four or more beacons in the environment for 3D localization. A lesser researched option is using Angle of Arrival (AoA) readings obtained from UWB antenna pairs to perform relative localization. In this paper, we present a UWB platform called ReLoki that can be used for ranging and AoA-based relative localization in 3D. To enable AoA, ReLoki utilizes the geometry of antenna arrays. In this paper, we present a system design for localization estimates using a Regular Tetrahedral Array (RTA), Regular Orthogonal Array (ROA), and Uniform Square Array (USA). The use of a multi-antenna array enables fully onboard infrastructure-free relative localization between participating ReLoki modules. We also present studies demonstrating sub-50cm localization errors in indoor experiments, achieving performance close to current ToF-based systems, while offering the advantage of not relying on static infrastructure.