Notch Filter Research Articles

Vital signs detection of moving targets using FMCW radar

Abstract Respiratory and heartbeat rates are crucial indicators for human health assessment. Compared to contact-based measurements, millimeter-wave radar detection of these vital signs avoids the discomfort caused by physical contact and better protects personal privacy, making it highly valuable for home health monitoring. The use of millimeter-wave radar for vital sign detection of the human body is mostly focused on targets in a stationary state at present. However, the human body may sway or even move during actual detection. This article proposes a non-contact vital sign detection method for moving targets. Compared with methods for detecting vital signs of stationary targets, detecting vital signs of moving targets requires determining the range bin where the targets are located continuously and extracting target phase information. The noise components such as movement and sway contained in the phase signal need to be removed. In this paper, moving target indication is used to remove static components, an adaptive range bin selection method is proposed to determine the range bin where the targets are located, and range bin selection fluctuation is smoothed using a moving average filter. The wavelet transform is used to decompose the phase signal, remove swaying noise based on autocorrelation function, and reconstruct the life signal for different scale factors. A bandpass filter is used to separate the respiratory and heartbeat signals, and a notch filter is designed to suppress respiratory harmonic signals. The experimental results show that the proposed method can separate vital signs signals from the phase signals of moving targets, achieving detection of respiration and heartbeat rate. The average accuracy of respiration and heartbeat rate detection is 94.7% and 95.5%, respectively.

Holographic Multi-Notch Filters Recorded with Simultaneous Double-Exposure Contact Mirror-Based Method

This study presents a novel simultaneous double-exposure contact mirror-based method for fabricating holographic multi-notch filters with dual operational central wavelengths. The proposed method leverages coupled wave theory, the geometric relationships of K-vectors, and a reflection-type recording setup, incorporating additional reflecting mirrors to guide the recording beams. To validate the approach, a holographic notch filter was fabricated using photopolymer recording materials, resulting in operational wavelengths of 531.13 nm and 633.01 nm. The measured diffraction efficiencies at these wavelengths were ηs = 52.35% and ηp = 52.45% for 531.13 nm, and ηs = 67.30% and ηp = 67.40% for 633.01 nm. The component’s performance was analyzed using s- and p-polarized spectral transmission intensities at various reconstruction angles, revealing polarization-independent characteristics under normal incidence and polarization-dependent behavior under oblique incidence. The study also explored the relationships between recording parameters, such as incident angle, wavelength, emulsion expansion, and dispersion. The findings demonstrate that the first operational central wavelength is primarily influenced by the recording wavelength, while the second is primarily determined by the incident angle, covering a range from visible light to near-infrared. This method offers significant potential for cost-effective, mass-produced filters in optoelectronic applications.

Adaptive control of an amplified piezoelectric-driven micropositioning stage based on notch filter structure inspiration and neural network online tuning

Abstract Piezoelectric-driven flexure micro/nanopositioning stages often exhibit a low-damping resonance mode, which can easily excite mechanical resonance during high-speed movement, and significantly impact the control system's stability, control bandwidth, and trajectory tracking accuracy. To mitigate the reliance on the precise modeling of stage dynamics inherent in current resonant controllers, an adaptive control method based on a back propagation (BP) neural network was designed to suppress resonance in real-time. First, a piezoelectric-driven flexure micro/nanopositioning stage system was constructed. Next, a feedback controller similar to a notch filter was designed, with bilinear transformation applied based on the system's inherent parameters to determine the initial values. Finally, the designed adaptive control method was tested through trajectory tracking experiments using a triangular wave signal. The experimental results showed that, when tracking the triangular wave signal, the maximum tracking error was reduced by 72.66% compared to proportional-integral (PI) control alone and by 68.66% compared to proportional integral control combined with a traditional notch filter. The tracking results demonstrate a significant improvement in the stage's stability and tracking accuracy.

Liquid Crystal Enables Extraordinarily Precise Tunability for a High‐Q Ultra‐Narrowband Filter Based on a Quasi‐BIC Metasurface

AbstractNotch filters usually involve high costs, great difficulties in processing, and very limited tunability. By coating a nematic liquid crystal (LC) layer onto a well‐designed quasi‐bound states in the continuum (quasi‐BICs) metasurface, this work designs and demonstrates a high‐Q tunable filtering system with precise tunability in the near‐infrared spectral range. Optimal structural parameters and the filtering performance are first determined by numerical simulations and then confirmed in experiments. The precise tunability is enabled by modifying the LC molecules’ principal axes with an applied voltage, where the least distinguishable central wavelength interval is smaller than 0.3 nm, and the largest Q factor extracted from experiments can be ≈256.1. Compared to most of the commercial notch filters that work in the visible region and have no tunability, this work achieves an ultra‐narrowband filtering system that features low manufacture difficulty and cost, and great control of light propagation. The proposed design also opens new avenues for developing BIC‐based high‐Q devices with enhanced signal‐to‐noise ratio and multifunctional properties.

Monitoring the Energy of a Cavity by Observing the Emission of a Repeatedly Excited Qubit.

The number of excitations in a large quantum system (harmonic oscillator or qudit) can be measured in a quantum nondemolition manner using a dispersively coupled qubit. It typically requires a series of qubit pulses that encode various binary questions about the photon number. Recently, a method based on the fluorescence measurement of a qubit driven by a train of identical pulses was introduced to track the photon number in a cavity, hence simplifying its monitoring and raising interesting questions about the measurement backaction of this scheme. A first realization with superconducting circuits demonstrated how the average number of photons could be measured in this way. Here we present an experiment that reaches single-shot photocounting and number tracking owing to a cavity decay rate 4 orders of magnitude smaller than both the dispersive coupling rate and the qubit emission rate. An innovative notch filter and pogo-pin-based galvanic contact makes possible these seemingly incompatible features. The qubit dynamics under the pulse train is characterized. We observe quantum jumps by monitoring the photon number via the qubit fluorescence as photons leave the cavity one at a time. Additionally, we extract the measurement rate and induced dephasing rate and compare them to theoretical models. Our method could be applied to quantum error correction protocols on bosonic codes or qudits.

Design of Concurrent Dual Band Low Noise Amplifier for WLAN Applications

This paper presents a dual band LNA CMOS designed for a Wireless Local Area Network (WLAN) application using CMOS 0.13-µm Silterra technology. The proposed design incorporates forward body bias technique with cascode and notch filter configuration to achieve both low power consumption and high gain. The simulation results demonstrate a total power consumption of 2.39 mW at a low supply voltage of 0.5 V, with a gain of 16 dB at 2.4 GHz and 12 dB at 5.2 GHz. Additionally, input return loss of -12.3 dB and -14.2 dB with noise figures of 2.93 dBm and 4.23 dBm were obtained at 2.4 GHz and 5.2 GHz, respectively. Overall, this research contributes to the development of dual band LNA designs for WLAN applications.

The 140 GHz notch filter development for millimeter-wave diagnostics protection on the stellarator Wendelstein 7-X

The notch filter plays a crucial role as a protective component in microwave diagnostics, primarily by addressing issues related to catastrophic interference. Designed for millimeter-wave diagnostics on the stellarator Wendelstein 7-X (W7-X), a WR-6 waveguide-based notch filter has been successfully developed to effectively isolate leakage from auxiliary heating gyrotrons operating at 140 GHz. The filter incorporates cylindrical cavities resonating at 140 GHz for the TE11p mode, with coupling structures that are designed and optimized for high-efficiency coupling. This configuration simplifies fabrication, thereby ensuring high-yield production. Experimental fabrication and in-house characterization confirm the notch filter's exceptional performance, with over 60 dB rejection in the vicinity of 140 GHz and low insertion loss (< 2 dB) above and below the notch frequency across a broad frequency bandwidth (121–138 GHz, 142–163 GHz). The utilization of this high-frequency structure fabrication technology can be applied to millimeter-wave diagnostics on other machines. In addition to the design elements of the notch filter, this paper also provides a detailed discussion of the fabrication process and methodology.

Dynamic modelling and a model-based control strategy of joint servo system for power transmission line inspection robot

Abstract The time-varying load inertia is one of the important dynamic characteristics of the power transmission line inspection robots (PTLIRs) in joint space, which can heavily affect the stability of the robot in the inspection process. In this paper, with considering the time-varying characteristics of load inertia, a method for modelling and control of the flexible joint servo system of the PTLIR is studied. First, the control system of the PTLIR is established based on the two inertia system. In order to calculate the load inertia, a dynamic model of the inspection robot is established. Then, the model-based notch filter is designed to improve dynamic performance of the robot, and suppress the vibration amplitude change which caused by the time-varying load inertia. Finally, the comparison of the control performance between the traditional control strategy and the model-based control strategy with notch filter are compared. The simulation results show that the paper can provide an effective tool for modelling and improving the stability of the PTLIR.

Mechanical Resonance Suppression Technique for Inertial Reference Unit Based on Band-pass Filter Disturbance Observer

Inertial reference unit (IRU) has been recognized as an effective method for photoelectric tracking and pointing system to suppress the disturbance. Its flexible support usually results in a low-frequency mechanical resonance within the bandwidth. Experimental identification indicates an obvious resonant peak at near 36.7Hz with an amplitude of 26.6dB. In this paper, disturbance observer based on band-pass filter (BPF-DOB) is combined with a notch filter to suppress the mechanical resonance. The asymmetry of the resonance peak and variation of the controlled object over the time are both addressed. Simulation and experimental results show that the stability accuracy of IRU system is improved to be 1.09 μrad, indicating an improvement of 9.9% relative to the traditional method and high robustness for time-varying resonance.

A wideband combined LNA‐filter in 22 nm FDSOI technology for satellite phased arrays

AbstractThis article introduces a new, low cost and complexity, wideband Ku/K‐band combined low‐noise amplifier (LNA) Filter designed for large satellite phased array systems in advanced 22 nm Fully Depleted Silicon on Insulator Technology. The LNA achieves the required 20 dB gain through a two‐stage configuration using the cascode configuration. To effectively reject the transmitter (TX) signal, the LNA integrates 4 distributed parallel LC notch filters. Measured IP1dB at 29 GHz (TX band) demonstrates a 25 dB increase compared to IP1dB at 19 GHz (RX Band), with a remarkable 15 dB enhancement over the LNA without the filter. The 1‐dB gain bandwidth spans from 16 to 21 GHz, representing a 27% fractional bandwidth. Over the entire bandwidth, input/output return losses exceed 10 dB, maintaining a low noise figure (NF) of less than 3.5 dB. Inclusion of two filters at the input and middle of the first stage results in approximately 0.6 dB of increase in NF when compared to the LNA without the filter.

Acoustic notch filter based on self-collimation sonic crystals

Utilizing the self-collimation effect in two-dimensional (2D) sonic crystals (SCs), we have proposed an acoustic notch filter which is composed of two perfect mirrors and a beam splitter. Numerical simulation shows that by properly designing the inside structure of the 2D SC, the self-collimated acoustic waves with a desired frequency can be trapped between the two mirrors, realizing the notch filtering function. Moreover, the frequency and bandwidth of the notch filter can be arbitrarily adjusted by changing the parameters of the internel structure, in a considerably broad band. Potential applications include acoustic communication and acoustic signal processing, especially for underwater circumstances.

Vibration Suppression of Multi-Stage-Blade AMB-Rotor Using Parallel Adaptive and Cascaded Multi-Frequency Notch Filters

Vibration Suppression of Multi-Stage-Blade AMB-Rotor Using Parallel Adaptive and Cascaded Multi-Frequency Notch Filters

Large stroke electromagnetic redundant actuated six degrees-of-freedom parallel compliant micropositioning stage

In this paper, a novel large stroke six degrees-of-freedom (6-DOF) electromagnetic redundant actuated micropositioning stage is proposed. The 6-DOF stage adopts a configuration that is composed of eight parallel driving branch chains. Each branch chain is driven by a voice coil motor and incorporates a parallelogram flexure mechanism and a decoupling mechanism for guidance and decoupling. The positioning stage is symmetrically arranged and possesses the advantages of simple structure and easy assembly. As a result, assembly errors are significantly reduced and positioning accuracy is enhanced. The decoupling mechanism uses a large stroke flexible ball joint that increases the motion range of the positioning stage and decouples the coupled motion, thereby enhancing the stability and accuracy of the stage. To evaluate the performance of the stage, static and dynamic analytical models of the 6-DOF stage are derived based on the compliance matrix method and the Lagrangian dynamic modeling method. Additionally, the accuracy of the analytical models and the static and dynamic performances of the positioning stage are verified through finite element analysis (FEA) and experimental testing. The experimental results demonstrate that the stage realizes a workspace of 2.06 mm × 2.02 mm × 3.1 mm × 23.4 mrad × 23.1 mrad × 14.9 mrad. Finally, to verify the tracking performance trajectory of the 6-DOF positioning stage, tracking experiments are performed using a controller that combines a proportional-integral controller and a notch filter.

Multi-domain awareness for compressed deepfake videos detection over social networks guided by common mechanisms between artifacts

The viral spread of massive deepfake videos over social networks has caused serious security problems. Despite the remarkable advancements achieved by existing deepfake detection algorithms, deepfake videos over social networks are inevitably influenced by compression factors. This causes deepfake detection performance to be limited by the following challenging issues: (a) interfering with compression artifacts, (b) loss of feature information, and (c) aliasing of feature distributions. In this paper, we analyze the common mechanism between compression artifacts and deepfake artifacts, revealing the structural similarity between them and providing a reliable theoretical basis for enhancing the robustness of deepfake detection models against compression. Firstly, based on the common mechanism between artifacts, we design a frequency domain adaptive notch filter to eliminate the interference of compression artifacts on specific frequency bands. Secondly, to reduce the sensitivity of deepfake detection models to unknown noise, we propose a spatial residual denoising strategy. Thirdly, to exploit the intrinsic correlation between feature vectors in the frequency domain branch and the spatial domain branch, we enhance deepfake features using an attention-based feature fusion method. Finally, we adopt a multi-task decision approach to enhance the discriminative power of the latent space representation of deepfakes, achieving deepfake detection with robustness against compression. Extensive experiments show that compared with the baseline methods, the detection performance of the proposed algorithm on compressed deepfake videos has been significantly improved. In particular, our model is resistant to various types of noise disturbances and can be easily combined with baseline detection models to improve their robustness.

Contributions of brain regions to machine learning-based classifications of attention deficit hyperactivity disorder (ADHD) utilizing EEG signals

Objective The study presented focuses on the creation of a machine learning (ML) model that uses electrophysiological (EEG) data to identify kids with attention deficit hyperactivity disorder (ADHD) from healthy controls. The EEG signals are acquired during cognitive tasks to distinguish children with ADHD from their counterparts. Methodology The EEG data recorded in cognitive exercises was filtered using low pass Bessel filter and notch filters to remove artifacts, by the data set owners. To identify unique EEG patterns, we used many well-known classifiers, including Naïve Bayes (NB), Random Forest, Decision Tree (DT), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), AdaBoost and Linear Discriminant Analysis (LDA), to identify distinct EEG patterns. Input features comprised EEG data from nineteen channels, individually and in combination. Findings Study indicates that EEG-based categorization can differentiate between individuals with ADHD and healthy individuals with accuracy of 84%. The RF classifier achieved a maximum accuracy of 0.84 when particular region combinations were used. Evaluation of classification performance utilizing hemisphere-specific EEG data yielded promising outcomes, particularly in the right hemisphere channels. Novelty The study goes beyond traditional methodologies by investigating the effect of regional data on categorization results. The contributions of various brain regions to these classifications are being extensively researched. Understanding the role of different brain regions in ADHD can lead to better diagnosis and treatment options for individuals with ADHD. The study of categorization ability, utilizing EEG data specific to each hemisphere, particularly channels in the right hemisphere region, provides further granularity to the findings.

Miniaturized spectrometers based on graded photonic crystal films.

Miniaturized spectrometers have become increasingly important in modern analytical and diagnostic applications due to their compact size, portability, and versatility. Despite the surge in innovative designs for miniaturized spectrometers, significant challenges persist, particularly concerning manufacturing cost and efficiency when devices become smaller. Here we introduce an ultracompact spectrometer design that is both cost-effective and highly efficient. The core dispersion element of this new design is a graded photonic crystal film, which is engineered by applying gradient stress during its fabrication. The film shows bandstop transmission spectral profiles, akin to a notch filter, enhancing light throughput compared to conventional narrowband filters. The spectral analysis, with a resolution of 5 nm and operating within the wavelength range of 450-650 nm, is conducted by reconstructing the spectrum from a series of such notch transmission profiles along the graded photonic crystal film, utilizing a sophisticated algorithm. This approach not only reduces manufacturing costs but also significantly improves the sensitivity (with a light throughput efficiency of 71.05%) and overall performance of the limitations of current technology, opening up new avenues for applications in diverse fields.

Design, modeling, and control of a long stroke compliant tip-tilt-piston micropositioning stage driven by voice coil motors.

In this paper, a long-stroke parallel compliant tip-tilt-piston micropositioning stage driven by voice coil motors (VCMs) is proposed. The stage is equipped with three sets of driving arms, which include a spherical hinge, VCM, and parallelogram guide mechanism, evenly spaced at 120° intervals. The spherical hinge is composed of orthogonal leaf-spring beams, and the VCM is embedded into the parallelogram mechanism to form a compact design. The compliance matrix method and the geometric method facilitated the determination of compliance in all six degree-of-freedom directions of the spherical hinge and the derivation of kinematic equations for decoupling the motion of the stage. In addition, finite element analysis was utilized to determine the maximum stroke and stress of the stage. To validate the proposed design, a stage prototype was constructed and subjected to experimental testing. Furthermore, a feedback controller was designed, integrating proportional integral controller, notch filter, and sliding mode controller feedforward. The experimental results indicate that the stage can achieve a long stroke of ±50.75 mrad × ±44.2 mrad × ±4.425mm, with the natural frequencies in the three-axis direction of 22.3 × 25.5 × 25.5Hz3. In addition, the maximum relative tracking error was maintained below 5.25%, highlighting the effectiveness of the control technique in achieving a high tracking performance.

A voltage-mode fully cascadable biquad with three CFOAs and grounded capacitors

In this paper, a new voltage-mode second-order multifunction filter with three current feedback operational amplifiers is developed. This circuit generates low-pass filter, band-pass filter (BPF), inverting-type BPF, notch filter, and all-pass filter (APF) responses with all gains. It has high input and low output impedances for all the filter responses. It also has the advantage of grounded two capacitors, which is essential for integrated circuit technology. It has orthogonally controllable features for all the filter responses except the APF one. However, one passive element matching condition is needed to obtain an APF response. Many simulations are carried out via the SPICE program, where 0.13 µm technology parameters are utilized. Furthermore, a few experiments are performed using the AD844s to see the performance of the developed filter in practice.

Combining optimal SASS (Sparsity Assisted Signal Smoothing) and notch filters for transient measurement signals denoising of large power generating unit

Denoising and harmonic interference removal from the measurement signal is crucial for accurate parameters calculation of a generating unit model. Determining the actual parameters values requires various unit transient signals data recorded during a well-defined testing procedure. However, the recorded signals usually contain noise and harmonic interferences which are difficult to remove due to a presence of different kinds of discontinuities.The paper presents a proposal of optimal denoising and harmonic interference removal method from transient measurement signals of 200 MW power generating unit. The method combines notch filters for harmonic rejection followed by SASS (Sparsity Assisted Signal Smoothing) algorithm for wideband noise rejection. Parameters of the notch filters as well as the SASS are determined using popular optimization algorithms (simulated annealing, Nelder-Mead simplex and gradient algorithm).Performance of the proposed method is compared to its direct Linear Time-Invariant (LTI) competitors such as low-pass and notch filters alone, notch and low-pass filters combined and to the optimal SASS method alone. The performance evaluation is based on a set of specially generated test signals which are using the developed mathematical model of the signals (to set the level of noise and interferences) as well as the mathematical model of the power generating unit (to provide the reference clean signals). The obtained results confirm that the optimal notch-SASS method might be a valuable noise removal tool for considered class of signals and leads to superior results than the LTI filters or the SASS method alone.

Suppressing the HIFU interference in ultrasound guiding images with a diffusion-based deep learning model

Background and objectivesIn ultrasound guided high-intensity focused ultrasound (HIFU) surgery, it is necessary to transmit sound waves at different frequencies simultaneously using two transducers: one for the HIFU therapy and another for the ultrasound imaging guidance. In this specific setting, real-time monitoring of non-invasive surgery is challenging due to severe contamination of the ultrasound guiding images by strong acoustic interference from the HIFU sonication. MethodsThis paper proposed the use of a deep learning (DL) solution, specifically a diffusion implicit model, to suppress the HIFU interference. We considered the images contaminated with HIFU interference as low-resolution images, and those free from interference as high-resolution. While suppressing HIFU interference using the diffusion implicit (HIFU-Diff) model, the task was transformed into generating a high-resolution image through a series of forward diffusion steps and reverse sampling. A series of ex-vivo and in-vivo experiments, conducted under various parameters, were designed to validate the performance of the proposed network. ResultsQuantitative evaluation and statistical analysis demonstrated that the HIFU-Diff network achieved superior performance in reconstructing interference-free images under a variety of ex-vivo and in-vivo conditions, compared to the most commonly used notch filtering and the recent 1D FUS-Net deep learning network. The HIFU-Diff maintains high performance with ‘unseen’ datasets from separate experiments, and its superiority is more pronounced under strong HIFU interferences and in complex in-vivo situations. Furthermore, the reconstructed interference-free images can also be used for quantitative attenuation imaging, indicating that the network preserves acoustic characteristics of the ultrasound images. ConclusionsWith the proposed technique, HIFU therapy and the ultrasound imaging can be conducted simultaneously, allowing for real-time monitoring of the treatment process. This capability could significantly enhance the safety and efficacy of the non-invasive treatment across various clinical applications. To the best of our knowledge, this is the first diffusion-based model developed for HIFU interference suppression.