Inverse Filtering Research Articles

Performance analysis of SMI filter for antenna array receiver in pulse interference environment

This paper analyzes the performance of sample matrix inversion (SMI) filter used by antenna array receivers in pulse interference environment. Firstly, from the perspective of comparison, it is proved that the theoretical optimal signal to interference noise ratio (SINR) of SMI filter under pulse interference is the same with that under continuous interferences. Then the convergence characteristics of SMI filter under pulse interference are deduced, and the relationship between the convergence speed and length of training samples and duty of interferences is given. Finally, the results of signal simulation are consistent with those of numerical analysis, which verifies the correctness of theoretical analysis. The results show that the convergence speed of SMI filter decreases under pulse interference, and the SMI filter needs more training samples to suppress the pulse interference effectively.

Laser-induced fluorescence spectroscopy for kinetic temperature measurement of xenon neutrals and ions in the discharge chamber of a radiofrequency ion source

Application of single-photon absorption laser-induced fluorescence (LIF) spectroscopy for non-intrusive measurement of neutral xenon and singly charged xenon ion kinetic temperatures in the discharge chamber of a gridded radiofrequency ion source is demonstrated. A LIF spectrum analysis approach including hyperfine structure reconstruction and inverse filtering (Fourier deconvolution) is outlined. Special focus is set on optimization of post-deconvolution filtering as well as retracing of deconvolution result imperfection due to hyperfine structure parameter uncertainty, incorrect natural linewidth, and saturation of the LIF signal. The corresponding contributions to the kinetic temperature estimation error are quantified via simulation of spectral lineshapes. Deconvolution of almost unsaturated LIF spectra recorded in the center of the ion source discharge chamber reveals that the neutral xenon and xenon ion kinetic temperatures range between approximately 500 and 700 K and, respectively, 700 and 1000 K depending on the radiofrequency power supplied to the discharge.

Tracking the trajectory of an object in a noisy environment with unknown statistics: A novel robust Kalman filter residue-based approach

A novel robust Kalman filter (KF)-based controller design approach is proposed to accurately track a specified trajectory under unknown stochastic disturbance, known deterministic disturbance, and measurement noise. The system is nonlinear and is approximated by a piecewise-linear dynamic model. The Box–Jenkins model is an augmented model of the signal and the disturbance, is non-controllable and observable, while the signal model is controllable and observable. An emulator-based two-stage identification is employed to obtain an accurate system model needed to design the robust controller. The system and its KF are identified, and the signal and output errors are estimated. From the identified models, the signal, its KF, the disturbance model, and the whitening filter are all obtained using balanced model reduction techniques. It is shown that the signal model is a transfer matrix description relating the system output and KF residual, and the residual is the whitened output error. The disturbance model is identified by inverse filtering. A new combined feedforward–feedback controller is designed and implemented using an internal model of the reference driven by both the error between the reference and the signal estimate, and by the feedforwarded reference signal. The proposed scheme was successfully evaluated on a simulated autonomously guided drone.

Automatic Inspection of Bridge Bolts Using Unmanned Aerial Vision and Adaptive Scale Unification-Based Deep Learning

Bolted connections are essential components that require regular inspection to ensure bridge safety. Existing methods mainly rely on traditional artificial vision-based inspection, which is inefficient due to the many bolts of bridges. A vision-based method using deep learning and unmanned aerial vision is proposed to automatically analyze the bridge bolts’ condition. The contributions are as follows: (1) Addressing the problems that motion blur often exists in videos captured by unmanned ariel systems (UASs) with high moving speed, and that bolt damage is hard to accurately detect due to the few pixels a single bolt occupies, a bolt image preprocessing method, including image deblurring based on inverse filtering with camera motion model and adaptive scaling based on super-resolution, is proposed to eliminate the motion blur of bolt images and segment them into subimages with uniform bolt size. (2) Addressing the problem that directly applying an object detection network for both bolt detection and classification may lead to the wrong identification of bolt damage, a two-stage detection method is proposed to divide bolt inspection into bolt object segmentation and damage classification. The proposed method was verified on an in-service bridge to detect bolts and classify them into normal bolts, corrosion bolts, and loose bolts. The results show that the proposed method can effectively eliminate the inherent defects of data acquired by UAS and accurately classify the bolt defects, verifying the practicability and high precision of the proposed method.

Glottal Airflow Estimation using Neck Surface Acceleration and Low-Order Kalman Smoothing.

The use of non-invasive skin accelerometers placed over the extrathoracic trachea has been proposed in the literature for measuring vocal function. Glottal airflow is estimated using inverse filtering or Bayesian techniques based on a subglottal impedance-based model when utilizing these sensors. However, deviations in glottal airflow estimates can arise due to sensor positioning and model mismatch, and addressing them requires a significant computational load. In this paper, we utilize system identification techniques to obtain a low order state-space representation of the subglottal impedance-based model. We then employ the resulting low order model in a Kalman smoother to estimate the glottal airflow. Our proposed approach reduces the model order by 94% and requires only 1.5% of the computing time compared to previous Bayesian methods in the literature, while achieving slightly better accuracy when correcting for glottal airflow deviations. Additionally, our Kalman smoother approach provides a measure of uncertainty in the airflow estimate, which is valuable when measurements are taken under different conditions. With its comparable accuracy in signal estimation and reduced computational load, the proposed approach has the potential for real-time estimation of glottal airflow and its associated uncertainty in wearable voice ambulatory monitors using neck-surface acceleration.

Data-assimilated time-lapse visco-acoustic full-waveform inversion: Theory and application for injected CO2 plume monitoring

Continuous seismic monitoring for quantifying CO2 plume migration and detection of any potential leakages in the subsurface is essential for the security of long-term anthropogenic carbon dioxide geologic storage. Traditional time-lapse full-waveform inversion (TLFWI) methods aim to map the CO2 distribution by estimating seismic velocity changes, but recent studies find that CO2-induced attenuation is an important complement to seismic velocity for tracking the CO2 plumes and even quantifying the CO2 saturation. We have developed a novel data-assimilated TLFWI method to construct high-resolution time-lapse velocity and attenuation changes from dense time-lapse monitoring data. This method consists of two theoretical developments: visco-acoustic full-waveform inversion (QFWI) and multiparameter hierarchical matrix-powered extended Kalman filter (mHiEKF). The method is capable of (1) posing temporal constraints to retrieve time-lapse information from dense monitoring data by using mHiEKF, (2) accurately recovering high-spatial-resolution velocity and attenuation perturbations using first-order equation system-based QFWI, and (3) providing the model uncertainty by estimating their model standard deviation. With numerical examples, we first find the effectiveness of the new QFWI on estimating accurate velocity and attenuation models simultaneously. Then, a CO2 leakage case and a realistic Frio-II CO2 monitoring case are presented to find the advantages and applicability of our data-assimilated QFWI method for estimating time-lapse changes using dense time-lapse monitoring surveys. By assimilating time-lapse seismic monitoring data over time, our data-assimilated QFWI method can improve the resolution of velocity and attenuation changes and decrease their model uncertainties.

Leveraging Domain Features for Detecting Adversarial Attacks Against Deep Speech Recognition in Noise

In recent years, significant progress has been made in deep model-based automatic speech recognition (ASR), leading to its widespread deployment in the real world. At the same time, adversarial attacks against deep ASR systems are highly successful. Various methods have been proposed to defend ASR systems from these attacks. However, existing classification based methods focus on the design of deep learning models while lacking exploration of domain specific features. This work leverages filter bank-based features to better capture the characteristics of attacks for improved detection. Furthermore, the paper analyses the potentials of using speech and non-speech parts separately in detecting adversarial attacks. In the end, considering adverse environments where ASR systems may be deployed, we study the impact of acoustic noise of various types and signal-to-noise ratios. Extensive experiments show that the inverse filter bank features generally perform better in both clean and noisy environments, the detection is effective using either speech or non-speech part, and the acoustic noise can largely degrade the detection performance.

A feedforward and feedback composite active noise reduction headset based on inverse filter frequency equalization and its DSP system implementation

The principle of active noise reduction headset is to reduce the original noise by generating inverted noise through the loudspeaker. The loudspeaker system will introduce spectrum distortion inevitably. This distortion will increase the complexity of the secondary channel model, which adversely affect identification of the primary channel in the real-time active noise reduction system. To improve the inherent frequency spectrum distortion of the speaker system, this paper proposes a new frequency equalization method based on inverse filtering. This method is applied to a feedforward and feedback compound active noise reduction earphone system, and a new active noise reduction headphone system is obtained. In order to improve the noise reduction effect, the pollution caused by the secondary sound source to the reference signal is compensated in the active noise reduction control scheme of this paper. Simulation and real-time noise reduction experiments based on DSP solution show that this new active noise reduction control system can achieve better noise reduction effects.

Decomposing stress wave interference in a cylindrical wooden medium using an inverse deconvolution filter.

Excitation of an embedded waveguide in the cross section plane of a cylindrical structure produces Rayleigh modes propagating primarily in circumferential regions of the propagating medium. In many applications, this region is critical to the overall strength of the structure. Using the through-transmission technique, the Rayleigh mode in cylindrical symmetry produces clockwise and counterclockwise trajectories that interfere with each other at the receiver, producing a composite energy response in the temporal domain that hinders the accurate mode characterization. This work presents a decomposition algorithm consisting of three processing steps: (1) analytical continuous wavelet transforms of the raw waveform; (2) frequency polynomial approximation of the inverse point spread function using L2 norm optimization; and (3) derivation of the inverse deconvolution filter via the dual derivative operator. This work demonstrates the mathematical formulation and algorithm implementation with numerical and empirical validations. The proposed decomposition filter can achieve the overall time and energy estimation accuracy with a relative root mean square error of 0.07. Its broader impact will enhance the parametric estimation of the diagnostic stress wave for material characterization.

ПРИМЕНЕНИЕ МЕТОДА КОРРЕКЦИИ БАЗИСА ДЛЯ УСТРАНЕНИЯ НЕОПРЕДЕЛЕННОСТИ ПРИ СИНТЕЗЕ ИНВЕРСНОГО ФИЛЬТРА

The process of linear filtering is considered as a process of representing a signal in an oblique coordinate system. An approach to the elimination of uncertainty of the "divide by zero" type in the synthesis of an inverse filter, based on the basis correction, is proposed.

A Feasibility Study of the Use of PZT Actuators for Active Control to Enrich Engine Sound

This study examines the feasibility of a novel active sound enrichment (ASE) system using piezoelectric actuators as sound generators and an inverse control filter to supplement poor engine sound at the driver’s ear location in a passenger car instead of using an interior audio system. The proposed ASE algorithm is developed as a purely feedforward control strategy to track the pre-defined target engine sound (three engine orders). Theoretical and experimental analyses are investigated in-depth on the vibro-acoustic characteristics of a PZT (lead zirconate titanate) actuator bonded on a steel plate and a dedicated control filter to supplement sound using an inverse method to compensate for the secondary path. The location of the PZT-plate actuator was carefully chosen to satisfy the causality condition and robustly stable control of the ASE algorithm. The experimental ASE system was set up in a test car, and the ASE algorithm was implemented in a real-time controller. The real-time ASE experiment results showed that the measured sound of the three orders was well supplemented as the tracking of the target sound was achieved robustly with small errors without any divergent instability. Thus, this study suggests that the proposed ASE system using the PZT-plate actuator and the dedicated control filter is a feasible method for enriching sound in cars, and this approach can be considered as a masking tool against some exotic noise frequently observed in various vehicles including electric vehicles.

Fractional-order inverse filters revisited: Equivalence with fractional-order controllers

The equivalence of fractional-order inverse filters with fractional-order controllers is demonstrated in this work. This is achieved by appropriately rewriting the filters transfer functions in order to clarify the correspondence between the gain and time-constant of the filters and the scaling factor and differentiation/integration constant of the controllers. Possible implementations of fractional-order inverse filters using second generation voltage conveyors are presented and an application example, related to the control of a motion system, is demonstrated for evaluating the behavior of the introduced structures.

Superior optimal inverse filtering of cutting forces in milling of thin-walled components

Measuring the cutting force when milling slender/thin-walled parts is difficult because of the large and long-lasting structural vibrations that cause inertial disturbances in the measured signals. Under these conditions, signal filtering is the only option to significantly extend the dynamic bandwidth of the device above 3 kHz. Non-parametric filters are typically preferred over parametric ones because they are more practical and easier to apply in industrial applications. Currently available parametric filters cannot address this problem because they are based on oversimplified transmissibility models or are affected by computational problems when the impulse responses of the device are excessively long. In this study, the novel non-parametric Superior Optimal Inverse Filter was developed to address the limitations of state-of-the-art filters. It is a non-trivial extension of the Optimal Inverse Filter to a higher dimensionality, and it can process long transients and generic (possibly aperiodic) signals. Thus, outstanding results were obtained both from modal analysis and from an actual case study, demonstrating the potential of the new filter for an effective and almost completely automatic cutting force dynamic compensation when milling thin-walled structures. The proposed filter was compared with parametric Kalman filters and with the existing non-parametric filters, and it offered a considerably better performance, particularly for compensating for cross disturbances and for input force position-dependent dynamics.

Correcting the effect of temperature on image quality of thermal imaging objectives by wavefront coding technique

The paper has proposed a method for correcting the effect of temperature on the imaging quality of thermal imaging systems by wavefront coding technology. A cubic phase mask was added to the aperture diaphragm of the thermal imaging objective to obtain a temperature-invariant point spread function (PSF). The received images will be of low quality but almost invariant with the change in temperature. An inverse filter was used to recover high-quality images over a variable temperature range. To demonstrate the effectiveness of the proposed method, a thermal imaging objective was used to experiment. The simulation results demonstrate that the proposed method can effectively eliminate the temperature influence on the image quality of the thermal imaging objective.

Employing Energy and Statistical Features for Automatic Diagnosis of Voice Disorders.

The presence of laryngeal disease affects vocal fold(s) dynamics and thus causes changes in pitch, loudness, and other characteristics of the human voice. Many frameworks based on the acoustic analysis of speech signals have been created in recent years; however, they are evaluated on just one or two corpora and are not independent to voice illnesses and human bias. In this article, a unified wavelet-based paradigm for evaluating voice diseases is presented. This approach is independent of voice diseases, human bias, or dialect. The vocal folds' dynamics are impacted by the voice disorder, and this further modifies the sound source. Therefore, inverse filtering is used to capture the modified voice source. Furthermore, the fundamental frequency independent statistical and energy metrics are derived from each spectral sub-band to characterize the retrieved voice source. Speech recordings of the sustained vowel /a/ were collected from four different datasets in German, Spanish, English, and Arabic to run the several intra and inter-dataset experiments. The classifiers' achieved performance indicators show that energy and statistical features uncover vital information on a variety of clinical voices, and therefore the suggested approach can be used as a complementary means for the automatic medical assessment of voice diseases.

Female adolescent singing voice characteristics: an exploratory study using LTAS and inverse filtering

Background and Aim: To date, little research is available that objectively quantifies female adolescent singing-voice characteristics in light of the physiological and functional developments that occur from puberty to adulthood. This exploratory study sought to augment the pool of data available that offers objective voice analysis of female singers in late adolescence. Methods: Using long-term average spectra (LTAS) and inverse filtering techniques, dynamic range and voice-source characteristics were determined in a cohort of vocally healthy cis-gender female adolescent singers (17 to 19 years) from high-school choirs in Aotearoa New Zealand. Non-parametric statistics were used to determine associations and significant differences. Results: Wide intersubject variation was seen between dynamic range, spectral measures of harmonic organisation (formant cluster prominence, FCP), noise components in the spectrum (high-frequency energy ratio, HFER), and the normalised amplitude quotient (NAQ) suggesting great variability in ability to control phonatory mechanisms such as subglottal pressure (Psub), glottal configuration and adduction, and vocal tract shaping. A strong association between the HFER and NAQ suggest that these non-invasive measures may offer complimentary insights into vocal function, specifically with regard to glottal adduction and turbulent noise in the voice signal. Conclusion: Knowledge of the range of variation within healthy adolescent singers is necessary for the development of effective and inclusive pedagogical practices, and for vocal-health professionals working with singers of this age. LTAS and inverse filtering are useful non-invasive tools for determining such characteristics.

Real-Time Visual Feedback in Singing Pedagogy: Current Trends and Future Directions

Singing pedagogy has increasingly adopted guide awareness through the use of meaningful real-time visual feedback. Technology typically used to study the voice can also be applied in a singing lesson, aiming at facilitating students’ awareness of the three subsystems involved in voice production—breathing, oscillatory and resonatory—and their underlying physiological, aerodynamical and acoustical mechanisms. Given the variety of real-time visual feedback tools, this article provides a comprehensive overview of such tools and their current and future pedagogical applications in the voice studio. The rationale for using real-time visual feedback is discussed, including both the theoretical and practical applications of visualizing physiological, aerodynamical and acoustical aspects of voice production. The monitorization of breathing patterns is presented, displaying lung volume as the sum of abdominal and ribcage movements signals. In addition, estimates of subglottal pressure are visually displayed using a subglottal pressure meter to assist with the shaping of musical phrases in singing. As to what concerns vibratory patterns of the vocal folds and phonatory airflow, the use of electroglottography and inverse filters is applied to monitor the phonation types, voice breaks, pitch and intensity range of singers of different music genres. These vocal features, together with intentional voice distortions and intonation adjustments, are also displayed using spectrographs. As the voice is invisible to the eye, the use of real-time visual feedback is proposed as a key pedagogical approach in current and future singing lessons. The use of such an approach corroborates the current trend of developing evidence-based practices in voice education.

A multi-channel hear-through filter design approach and its applications

Sound characteristics change when propagating through materials and structures, such as vehicle cabins or space partitions. These structures usually block the sound propagation path and cause significant distortion to the sound heard by the other side of the structures while, in many applications, clear speech communication is needed. Especially during the Pandemic of Covid-19, it has become common to have space partitions at face-to-face service locations, for example, places providing food or banking services, for the prevention of virus spread. However, the degraded conversation sound quality caused by these partitions can negatively affects the service quality. A multi-channel active hear-through system is developed in the current work to provide a solution to provide more realistic sound environments for conversation through partitions which can preserve both the spectrum and the spatial distribution of the original sound field. This would also be useful for the improvement of augmented reality experiences and sound transmission quality in divided spaces. Compared with a direct inverse filter design, the coupling effect across channels and the superposition effect of original and reproduced sound are considered in the proposed method.

Компенсация искажений сигналов при распространении по трансионосферным радиолиниям с использованием глобальной модели земной ионосферы

A description is given of distortions of complex envelopes of digital signals during their propagation along transionospheric channels, the effect of which is equivalent to linear filtering. It is shown that signal distortions due to the dispersion properties of the earth's ionosphere cause the occurrence of interference noise which reduces the reliability of information transmission. It is noted that the effect of digital signal processing methods at reception, which reduce the distorting effect of interference is to form a linear filter with an inverse transmission coefficient relative to the transionospheric channels. A method for forming the inverse filter using the global model of the earth's ionosphere Klobuchar, developed and intensively used in the GPS satellite navigation system to improve the accuracy of navigation measurements is considered. A detailed description of this method is given, which is based on estimating the total electron content of a transionospheric channels using the considered Klobuchar model. Limitations in the application of the method under consideration are determined.

Calculation of Band-Pass Filters with Fixed Frequencies of Infinite Attenuation

Introduction. When calculating band-pass filters (BPF) with infinite attenuation frequencies using the frequency conversion method, the parameters of the prototype – an inverse or quasi-elliptic low-pass filter (LPF) – are recalculated into BPF parameters according to conventional formulas. Using the selected low-pass filter cutoff frequency and the Q-factor of the band-pass filter, one can select at their discretion only one infinite attenuation frequency (attenuation pole). In order to suppress a pair of concrete frequencies in the attenuation band, the synthesis of BPF should initially fix the frequencies of maximum attenuation and the central frequency of the filter. The reverse transition toward the frequency response parameters of a low-frequency prototype is carried out using frequency conversion formulas.Aim. To develop of a method for calculating band-pass filters with fixed attenuation poles.Materials and methods. Odd-order filters with an additional capacitor in the transverse branch of the П-link and an inductance in the longitudinal branch of the Т-link were used as low-frequency prototypes of the BPF with attenuation poles. Approximation of the frequency response of a low-frequency prototype (inverse or quasi-elliptical LPF) was performed by methods based on solving systems of nonlinear equations.Results. A realizable transfer function (TF) of an n-th order LPF with attenuation poles was written as the ratio of the product of binomials and a polynomial of power n with real coefficients. Systems of equations were derived to determine amplitude-frequency response coefficients with a given frequency of maximum attenuation interference for both types of filters. Analytical expressions for the TF of the low frequency prototypes of 3th and 5th orders were recorded through the capacitances of the BPF circuits tuned to the central and suppressed frequencies, thus allowing the desired capacitances to be directly calculated. The BPF inductances were determined by formulas expressing the dependences of the BPF central frequency on the circuits parameters, taking into account the relationships given in the article. An example of calculating a 10th order quasi-elliptic BPF was provided.Conclusion. The proposed method can be used to determine the BPF parameters directly, without an intermediate calculation and subsequent transformation of the LPF prototype parameters. The given analytical expressions for the frequency response of the П- and Т-shaped BPFs of the 6th and 10th orders make it possible to verify the performed calculations and to correct the frequency response using inductances, when replacing the calculated capacitance values with their standard values.