Proposed Signal Processing Algorithm Research Articles

Use of a spatially distributed in-phase antenna to increase the noise immunity of signal reception

Objectives. Radio-technical information transmission systems are widely used in various sectors of our life, not only for telecommunications and associated domestic needs, but also for the functioning of various special services, such as emergency response units, which increasingly use robotic complexes in the course of their work. In the event of an emergency, robot devices can be used to get in under rubble, in concrete pipes or other municipal facilities, which typically result in a sharp deterioration of the necessary conditions for the propagation of radio waves. In this regard, the problem of ensuring reliable communication with the robotic complex becomes rather acute. The aim of the present work is to reduce the effect of multipath propagation of radio waves in the communication channel under complex interference conditions.Methods. The methods of statistical radio engineering and mathematical modeling are used according to optimal signal reception theory.Results. The presented model for a multi-element, spatially-distributed, in-phase receiving antenna of various configurations, featuring an electronically adjustable radiation pattern, is designed to ameliorate the multipath nature of signal propagation. A simulation of a multipath communication channel was carried out in the presence of one main and three reflected beams of radio wave propagation, as well as with harmonic interference at two angles of its arrival and different frequency detuning relative to the frequency of the useful signal. The probability of a bit error when receiving discrete information using the proposed antenna is estimated.Conclusions. The proposed signal processing algorithm on the receiving side can be used to partially compensate for the influence of the multipath effect. As a result, the noise immunity of information reception in comparison with reception on an omnidirectional antenna with one antenna element increases: for a bit error probability of 10−3, the energy gain ranges from 2 dB for two beams to 7–10 dB for three or four beams. In the presence of concentrated harmonic interference in the radio channel, its simultaneous spatial (by the antenna) and spectral (by the demodulator) filtering is also observed, the effectiveness of which depends on the direction of arrival and the frequency detuning of the interference, which also leads to a significant decrease in the error probability.

Enhanced phase method of signal detection for ultrasonic magnetostriction defectoscopy of power equipment

The magnetostrictive method of ultrasonic flaw detection has certain advantages, in particular, the ability to control objects with complex geometry, at their high temperature, the ability to control dry contact between the transducer and the object, difficult access to the controlled area, etc. The peculiarities of the generation of ultrasonic waves by magnetostrictive transducers and their distribution in control objects determine the low level of the signal/noise ratio, which limits the possibilities of practical application of this method. The aim of the paper is to improve the phase method for detecting signals of magnetostrictive receivers with a low signal/noise ratio and to check the effectiveness of the proposed technical solution for solving problems of non-destructive testing of energy equipment elements using magnetostrictive defectoscopes. The paper discusses the phase method of detecting radio pulse signals of magnetostrictive converters against the background of additive noise, which is based on a combination of the capabilities of the discrete Hilbert transformation, which makes it possible to determine the envelope and phase of signals, and methods of statistical processing of the results of phase measurements. The proposed signal processing algorithm was studied both in a model experiment and when processing real magnetostrictive defectoscope signals. The proposed method makes it possible to detect radio pulse signals with a signal/noise ratio close to 1. The reliability of the obtained data is confirmed by the results of computer simulation. The considered method of detecting signals can be used in ultrasonic magnetostrictive defectoscopes and other diagnostic systems operating in conditions of reduced signal/noise ratio. Keywords: magnetostrictive defectoscope, ultrasonic defectoscopy, phase methods of signal processing, Hilbert transform, envelope, phase, sample resulting length of the vector.

Evaluation of continuous fiber Bragg grating and signal processing method for hotspot detection at cryogenic temperatures

The recent adoption of high-T c superconductor (HTS) wires for ultra-high field magnet windings provide great promise for future applications, such as high-power generators and Tokamak fusion reactors. However, an open issue with the use of HTS is the challenge of rapidly detecting a hot spot which could lead to a quench. Optical fiber sensors have been shown to be promising alternatives to the voltage-based quench detection method. In this paper, we report on ultra-long fiber Bragg gratings (ULFBG) for hotspot detection at cryogenic temperatures using a new detection algorithm. This novel sensing system is suitable for applications in which solely the occurrence of a hotspot but not its precise location is of importance. This is the case e.g. for quench detection in HTS. The developed system provides the advantages of cost reduction and faster response time compared to conventional FBGs with wavelength-division multiplexing and continuous FBGs with time-division multiplexing, respectively. We demonstrate the functionality of the system for the ULFBG with a grating length of 100 mm and 500 mm at 77 K and 90 K respectively. The ULFBG is shown to respond as fast as conventional FBG, to a hot spot as small as 1 K temperature rise. Furthermore, using the proposed signal processing algorithm, ULFBG exhibits much higher signal to noise ratio than that from the conventional FBG. It is believed that artificial intelligence based technique can assist the signal processing algorithm in detecting a small hot spot more rapidly from the big spectral data in real-time.

Real-Time Detection of Electric Field Signal of a Moving Object Using Adjustable Frequency Bands and Statistical Discriminant for Underwater Defense

The electric field method is robust in detecting underwater moving target objects in acoustically noisy conditions, such as a shallow water environment. However, it requires an enhanced signal processing algorithm to cope with the time-variant sea noise which distorts the target response and decreases data quality and detection performance. We propose a novel signal processing algorithm with superior performance to solve this problem. The proposed signal processing algorithm decomposes a measured signal into several frequency coefficients. It then extracts the target response using the coefficients in a frequency range chosen by a real-time statistical discriminant depending on the noise. We verify the effectiveness of the proposed signal processing algorithm through a field experiment, which can be a challenging task for conventional algorithms. We expect that this study will contribute to several fields of anomaly detection, especially in offshore defense and surveillance.

Application of Derivative Transform Spectroscopy in Gas Detection

Digital filtering technique is of great significance in real-time signal processing and analysis, but the stability, efficiency and flexibility of filter algorithm are important indicators to reflect its application value. In this paper, an adaptive derivative transformation based on Savitzky-Golay filter algorithm was proposed for laser absorption spectroscopy analysis. To demonstrate this analysis algorithm, first-order and second-order derivative spectroscopy are evaluated for the analysis of infrared methane absorption spectra, and compared with the original direct absorption spectral signals. The results indicated that the proposed signal processing algorithm has good performance on noise suppression and spectral resolution improvement, and the 2nd derivative spectroscopy shows better de-noising efficiency.

A Novel Signal Processing Technique for Ku-Band Automobile FMCW Fully Polarimetric SAR System Using Triangular LFM

This article presents a novel signal technique for Ku-band automobile frequency-modulated continuous-wave fully polarimetric synthetic aperture radar (FMCW PolSAR) system using triangular linear frequency modulation (LFM). Our proposed system shows the first utilizations of triangular LFM for an FMCW PolSAR. The proposed signal processing algorithm is based on the range Doppler algorithm (RDA). We developed an FMCW PolSAR system that transmits triangular LFM signals, which are used less frequently than sawtooth LFM in an SAR sensor. Using a theoretical background, we describe its configuration and how it works. We propose the novel processing solution, which forms two kinds of single-polarization images from a raw data set and is suitable for our system. We obtained all four kinds of single-polarization images from two raw data sets while using the triangular LFM. In comparison, when using sawtooth LFM, we obtained the four images from four raw data sets by repeating the RDA four times. The proposed method simplifies the FMCW PolSAR system configuration and the processing algorithm. We collected FMCW PolSAR raw data from an experimentally equipped automobile while maintaining a constant speed on a highway. The proposed algorithm and system were validated by processing a high-resolution FMCW PolSAR image.

Low-Cost Experimental Methodology for the Dynamic Model Approximation of Multirotor Actuators

A methodology for the experimental modelling of the electric actuators of a multirotor is presented in this work. These actuators are usually brushless DC motors which are driven by electronic speed controllers in an open loop. The duty cycle of a PWM signal, generated by the electronic control unit, is the input of the electronic controller. However, during the control design procedure for the multirotor, it is important to account with a model of the actuators as its dynamical features define the closed-loop performance of the overall aircraft. Hence, a procedure, based on low-cost electronic components, to obtain approximated transfer functions of the actuators of a multirotor is presented. Moreover, as the proposed signal processing algorithms are simple, the computational capabilities of the required embedded system are also low. Given that different control schemes require different information from the actuator, two models were obtained: a duty cycle vs. angular velocity transfer function and a duty cycle vs. consumed current transfer function. The effectivity of the proposal is validated with experimental results on common electric actuators of a multirotor.

DIGITAL HEARING AID SIGNAL PROCESSING SYSTEM USING ANDROID PHONE

Objective: The objective of this research is to propose an Android-based digital hearing aid signal processing algorithm with following key features:(1) Regenerated audio match the patient-specific pattern of hearing loss, (2) noise reduction, and (3) provide flexibility to the users.Methods: The proposed signal processing algorithm is designed based on the specific hearing loss of the hearing disorder patient using inverse Fouriertransform; besides, noise reduction feature is included in the digital algorithm design as well. Proposed digital algorithm has been implemented intoan Android-based smartphone and its performance has been tested under real-time condition.Results: Simulation results show that the frequency response of the proposed digital hearing aid signal processing algorithm is in agreement withthe initial theoretical design that was carried out based on the hearing impaired patient’s audiogram. The proposed algorithm has been implementedin the Android-based smartphone and tested in real time. Results show that most of the patients are satisfied with the regenerated audio quality.According to patient’s comments, the regenerated audio is clear and the users are allowed to control the volume level. Besides, no obvious hearinglatency can be detected.Conclusion: Audio signals generated by the proposed digital signal processing algorithm show similar audio signal frequency response in boththeoretical design and MATLAB simulation results. The only difference between the design and simulation results is the amplification levels. Theproposed algorithm provides flexibility to the users by allowing them to choose the desired amplification level. In real-time testing, the proposedAndroid-based digital hearing aid is able to reduce noise level from the surrounding and the output processed speech match the patient-specifichearing loss.

An open-loop system design for deep space signal processing applications

A novel open-loop system design with high performance is proposed for space positioning and navigation signal processing. Divided by functions, the system has four modules, bandwidth selectable data recorder, narrowband signal analyzer, time-delay difference of arrival estimator and ANFIS supplement processor. A hardware-software co-design approach is made to accelerate computing capability and improve system efficiency. Embedded with the proposed signal processing algorithms, the designed system is capable of handling tasks with high accuracy over long period of continuous measurements. The experiment results show the Doppler frequency tracking root mean square error during 3 h observation is 0.0128 Hz, while the TDOA residue analysis in correlation power spectrum is 0.1166 rad.

A Signal Processing Algorithm Based on 2D Matched Filtering for SSAR

This study discusses a smart radar antenna scanning mode that combines features of both the sector-scan mode used for conventional radar and the line-scan mode used for synthetic aperture radar (SAR) and achieves an application of the synthetic aperture technique in the conventional sector-scan (mechanically scanned) radar, and we refer to this mode as sector-scan synthetic aperture radar (SSAR). The mathematical model is presented based on the principle of SSAR, and a signal processing algorithm is proposed based on the idea of two-dimensional (2D) matched filtering. The influences of the line-scan range and speed on the SSAR system are analyzed, and the solution to the problem that the target velocity is very high is given. The performance of the proposed algorithm is evaluated through computer simulations. The simulation results indicate that the proposed signal processing algorithm of SSAR can gather the signal energy of targets, thereby improving the ability to detect dim targets.

Testing of composite materials using advanced NDT methods

PurposeThe purpose of this paper is to present capabilities of terahertz imaging technology in case of various composite materials and to propose a new defect detection algorithm.Design/methodology/approachThis paper first discusses an applicability of the terahertz technique in composite materials inspection. It then describes source of terahertz radiation (photoconductive antenna) and general structure of terahertz time domain imaging system. Next the terahertz imaging results of composite anticorrosion coating, glass‐ and carbon‐fiber‐reinforced laminates are presented. Then the signal processing and identification scheme based on time domain A‐scan signal equalization and C‐scan thresholding is presented. Data processed in this way are parameterized and defect identification database is prepared. The proposed procedure is verified using the exemplary inspection results of glass‐fiber laminate delamination. Finally, some comparison of terahertz time domain inspection with low energy digital radiography is presented.FindingsThis paper shows terahertz imaging as a well‐suited technique for composite structures inspection. The terahertz imaging results of composite anticorrosion coating, glass‐ and carbon‐fiber‐reinforced laminates are presented. An application of proposed signal processing algorithm enables accurate defects detection and effective data collection for identification database purpose.Originality/valueThe paper provides an insight into the potential of terahertz imaging of various composite structures. Proposed signal processing and defects detection scheme is applicable to wide range of composite structures.

Prediction of hydrophobic regions effectively in transmembrane proteins using digital filter

The hydrophobic effect is the major factor that drives a protein molecule towards folding and to a great degree the stability of protein structures. Therefore the knowledge of hydrophobic regions and its prediction is of great help in understanding the structure and function of the protein. Hence determination of membrane buried region is a computationally intensive task in bioinformatics. Several prediction methods have been reported but there are some deficiencies in prediction accuracy and adaptability of these methods. Of these proteins that are found embedded in cellular membranes, called as membrane proteins, are of particular importance because they form targets for over 60% of drugs on the market. 20-30% of all the proteins in any organism are membrane proteins. Thus transmembrane protein plays important role in the life activity of the cells. Hence prediction of membrane buried segments in transmembrane proteins is of particular importance. In this paper we have proposed signal processing algorithms based on digital filter for prediction of hydrophobic regions in the transmembrane proteins and found improved prediction efficiency than the existing methods. Hydrophobic regions are extracted by assigning physico-chemical parameter such as hydrophobicity and hydration energy index to each amino acid residue and the resulting numerical representation of the protein is subjected to digital low pass filter. The proposed method is validated on transmembrane proteins using Orientation of Proteins in Membranes (OPM) dataset with various prediction measures and found better prediction accuracy than the existing methods.

High Precision Signal Processing Algorithm for White Light Interferometry.

A new signal processing algorithm for absolute temperature measurement using white light interferometry has been proposed and investigated theoretically. The proposed algorithm determines the phase delay of an interferometer with very high precision (≪ one fringe) by identifying the zero order fringe peak of cross-correlation of two fringe scans of white light interferometer. The algorithm features cross-correlation of interferometer fringe scans, hypothesis testing and fine tuning. The hypothesis test looks for a zero order fringe peak candidate about which the cross-correlation is symmetric minimizing the uncertainty of mis-identification. Fine tuning provides the proposed algorithm with high precision sub-sample resolution phase delay estimation capability. The shot noise limited performance of the proposed algorithm has been analyzed using computer simulations. Root-mean-square (RMS) phase error of the estimated zero order fringe peak has been calculated for the changes of three different parameters (SNR, fringe scan sample rate, coherence length of light source). Computer simulations showed that the proposed signal processing algorithm identified the zero order fringe peak with a miss rate of 3 × 10-4 at 31 dB SNR and the extrapolated miss rate at 35 dB was 3 × 10-8. Also, at 35 dB SNR, RMS phase error less than 10-3 fringe was obtained. The proposed signal processing algorithm uses a software approach that is potentially inexpensive, simple and fast.

An All Fiber White Light Interferometric Absolute Temperature Measurement System.

Recently the author of this article proposed a new signal processing algorithm for an all fiber white light interferometer. In this article, an all fiber white light interferometric absolute temperature measurement system is presented using the previously proposed signal processing algorithm. Stability and absolute temperature measurement were demonstrated. These two tests demonstrated the feasibility of absolute temperature measurement with an accuracy of 0.015 fringe and 0.0005 fringe, respectively. A hysteresis test from 373K to 873K was also presented. Finally, robustness of the sensor system towards laser diode temperature drift, AFMZI temperature drift and PZT non-linearity was demonstrated.

A Phased Array-based Method for Damage Detection and Localization in Thin Plates

A method for damage localization based on the phased array idea has been developed. Four arrays of transducers are used to perform a beam-forming procedure. Each array consists of nine transducers placed along a line, which are able to excite and register elastic waves. The A0 Lamb wave mode has been chosen for the localization method. The arrays are placed in such a way that the angular difference between them is 45° and the rotation point is the middle transducer, which is common for all the arrays. The idea has been tested on a square aluminium plate modeled by the Spectral Element Method. Two types of damage were considered, namely distributed damage, which was modeled as stiffness reduction, and cracks, modeled as separation of nodes between selected spectral elements. The plate is excited by a wave packet. The whole array system is placed in the middle of the plate. Each linear phased array in the system acts independently and produces maps of a scanned field based on the beam-forming procedure. These maps are made of time signals (transferred to space domain) that represent the difference between the damaged plate signals and those from the intact plate. An algorithm was developed to join all four maps. The final map is modified by proposed signal processing algorithm to indicate the damaged area of the plate more precisely. The problem for damage localization was investigated and exemplary maps confirming the effectiveness of the proposed system were obtained. It was also shown that the response of the introduced configuration removes the ambiguity of damage localization normally present when a linear phased array is utilized. The investigation is based exclusively on numerical data.

A Systems Approach for Data Compression and Latency Reduction in Cortically Controlled Brain Machine Interfaces

This paper suggests a new approach for data compression during extracutaneous transmission of neural signals recorded by high-density microelectrode array in the cortex. The approach is based on exploiting the temporal and spatial characteristics of the neural recordings in order to strip the redundancy and infer the useful information early in the data stream. The proposed signal processing algorithms augment current filtering and amplification capability and may be a viable replacement to on chip spike detection and sorting currently employed to remedy the bandwidth limitations. Temporal processing is devised by exploiting the sparseness capabilities of the discrete wavelet transform, while spatial processing exploits the reduction in the number of physical channels through quasi-periodic eigendecomposition of the data covariance matrix. Our results demonstrate that substantial improvements are obtained in terms of lower transmission bandwidth, reduced latency and optimized processor utilization. We also demonstrate the improvements qualitatively in terms of superior denoising capabilities and higher fidelity of the obtained signals.

Absolute Temperature Measurement using White Light Interferometry

Recently a new signal processing algorithm for white light interferometry was presented. In this paper, the proposed signal processing algorithm was applied for absolute temperature measurement using white light interferometry. Stability testing and absolute temperature measurement were demonstrated. Stability test demonstrated the feasibility of absolute temperature measurement with an accuracy of 0.015 fringe. The test also showed that the absolute temperature measurement system using white light interferometry is capable of obtaining the theoretical minimum detectable change (0.0005 fringe), which is consistent with the performance predicted by the proposed signal processing algorithm.

Weighted median filters with sigma-delta modulation encoding

Digital decimation filters play a fundamental role in oversampled sigma-delta A/D decoders. In this paper, we first show that weighted median (WM) filtering of a demodulated sequence (at the Nyquist rate) can be implemented concurrently in the A/D decoder. Through a simple modification of the binary time-series outputted by the A/D modulator, the sequence obtained after the sigma-delta modulation (SDM) decoder is shown to be equivalent to WM filtering the multilevel sequence at the Nyquist rate. Second, we show that WM filters can be used for SDM decimation filters and that these filters are readily implemented in the SDM binary domain. A very promising characteristic of SDM converters equipped with WM decimating filters is that sharp discontinuities (edges) can be preserved and acquired. Thus, the bandlimited constraint imposed on the input signals can be relaxed making SDM more attractive to A/D conversion of signals containing sharp transitions. The proposed signal processing algorithms, in essence, combine A/D sigma-delta converters and WM filters into a single programmable system.