Signal Processing Scheme Research Articles

Scheme of Signal Processing in a Multimode Communication Receiver Based on Convolutional Neural Networks

Scheme of Signal Processing in a Multimode Communication Receiver Based on Convolutional Neural Networks

Forward-Looking Passive Radar With Non-Uniform Linear Array for Automotive Applications

With the rapid and growing spread of automotive radar systems in modern vehicles, the problem of their mutual interference is becoming a major safety concern. This paper considers the use of receive-only sensors onboard the vehicles, which exploit an external illumination source to provide automotive radar functionalities. The passive radar paradigm would solve the problem of mutual interference, allowing different systems to share the same transmitted signal. A preliminary analysis of the feasibility of this concept is carried out, exploiting real-world transmitters of opportunity. The potentialities offered by both satellite and ground-based illuminators are investigated and the expected performance is evaluated in terms of achievable coverage and spatial resolution. Aiming to enable a practical implementation of the proposed concept, an appropriate signal processing scheme is proposed to obtain maps of the observed scene. A Doppler beam sharpening approach is adopted to discriminate and localize stationary scatterers in azimuth based on the differences in their relative Doppler shift. The problem of left/right ambiguity arising from the forward-looking geometry is tackled by exploiting an array of few antenna elements on receive. Specifically, an ambiguity removal approach is proposed, based on digital beam pattern adaptation, designed to maximise the response in the desired direction and suppress unwanted echoes from the corresponding ambiguous one. The effectiveness of this approach is further improved by cascading an apodization technique that prevents the undesirable increase in the noise level. Moreover, some criteria are introduced for the design of the antenna layout, resorting to non-uniform linear array configurations. The proposed system is tested against a simulated environment, where the multi-channel signal processing, combined with a properly designed array layout, is shown to provide an unambiguous mapping of the observed scene over wide angular sectors, even operating with few antenna elements on receive.

VWM-DCRNN: A Method of Combining Signal Processing With Deep Learning for Fault Diagnosis in Single-Phase PWM Rectifier

Based on variational mode decomposition and dual model of convolutional recurrent neural network (VMD-DCRNN), a novel diagnosis method is proposed to discover the faults of IGBTs, diodes and series resonant circuit in single-phase pulse width modulation (PWM) AC-DC rectifier, an important part of traction power supply system of high-speed railway. By virtue of the combination of signal processing and deep learning schemes, the multi-scale feature information for fault diagnosis is extracted by regarding the input current of the rectifier and the voltage of dc side as the original signal. More clearly, VMD is adopted to decompose the original signal to a series of intrinsic mode function components (IMFs). Then, the submodel of current is designed to detect the fault types of IGBTs and diodes. Meanwhile, the submodel of voltage is established to identify the fault types of series resonant circuit. These IMFs are fed into DCRNN consisting of the two submodels for training and testing. Finally, the features extracted from the two submodels are integrated and converted to label space to complete fault diagnosis. Experimental results show that the proposed VMD-DCRNN algorithm is superior to the single-channel models, reaching 96.27%.

Head movement and its relation to hearing.

Head position at any point in time plays a fundamental role in shaping the auditory information that reaches a listener, information that continuously changes as the head moves and reorients to different listening situations. The connection between hearing science and the kinesthetics of head movement has gained interest due to technological advances that have increased the feasibility of providing behavioral and biological feedback to assistive listening devices that can interpret movement patterns that reflect listening intent. Increasing evidence also shows that the negative impact of hearing deficits on mobility, gait, and balance may be mitigated by prosthetic hearing device intervention. Better understanding of the relationships between head movement, full body kinetics, and hearing health, should lead to improved signal processing strategies across a range of assistive and augmented hearing devices. The purpose of this review is to introduce the wider hearing community to the kinesiology of head movement and to place it in the context of hearing and communication with the goal of expanding the field of ecologically-specific listener behavior.

Demodulation of temperature with high spatial resolution based on RDTS system

Measurement of temperature along the fiber based on Raman distributed temperature sensing (RDTS) system has been studied and applied broadly. However, the minimum fiber length and temperature change required to correctly obtain the actual temperature variation in periodic regions (PRs) are limited by the systematic spatial resolution of the order of meters. To improve the spatial resolution of temperature measurement, we propose a novel signal processing scheme that firstly associates the position of each region with the relevant sampling points in the temperature rise curve, then combines the theoretically and experimentally derived relation that different intensities can be obtained by sensing temperature with the luminous flux at different locations within the pulsed light, and finally separates the Raman intensity generated by each region from the temperature rise curve of PRs. The experimental results show that the temperature demodulation of five PRs with a length of 0.5 m can be achieved with an average accuracy of ±2.3 °C. The proposed scheme improves the spatial resolution of the conventional RDTS system from 4 m to 0.5 m and provides a new solution for the temperature monitoring of PRs.

The effects of estimation accuracy, estimation approach, and number of selected channels using formant-priority channel selection for an "n-of-m" sound processing strategy for cochlear implants.

Previously, selection of l channels was prioritized according to formant frequency locations in an l-of-n-of-m-based signal processing strategy to provide important voicing information independent of listening environments for cochlear implant (CI) users. In this study, ideal, or ground truth, formants were incorporated into the selection stage to determine the effect of accuracy on (1) subjective speech intelligibility, (2) objective channel selection patterns, and (3) objective stimulation patterns (current). An average +11% improvement (p < 0.05) was observed across six CI users in quiet, but not for noise or reverberation conditions. Analogous increases in channel selection and current for the upper range of F1 and a decrease across mid-frequencies with higher corresponding current, were both observed at the expense of noise-dominant channels. Objective channel selection patterns were analyzed a second time to determine the effects of estimation approach and number of selected channels (n). A significant effect of estimation approach was only observed in the noise and reverberation condition with minor differences in channel selection and significantly decreased stimulated current. Results suggest that estimation method, accuracy, and number of channels in the proposed strategy using ideal formants may improve intelligibility when corresponding stimulated current of formant channels are not masked by noise-dominant channels.

Experimental Demonstration of In-Memory Computing in a Ferrofluid System.

Magnetic fluids are excellent candidates for several important research fields including energy harvesting, biomedical applications, soft robotics, and exploration. However, notwithstanding relevant advancements such as shape reconfigurability, that have been demonstrated, there is no evidence for their computing capability, including the emulation of synaptic functions, which requires complex non-linear dynamics. Here, it is experimentally demonstrated that a Fe3 O4 water-based ferrofluid (FF) can perform electrical analogue computing and be programmed using quasi direct current (DC) signals and read at radio frequency (RF) mode. Features have been observed in all respects attributable to a memristive behavior, featuring both short and long-term information storage capacity and plasticity. The colloid is capable of classifying digits of a 8×8 pixel dataset using a custom in-memory signal processing scheme, and through physical reservoir computing by training a readout layer. These findings demonstrate the feasibility of in-memory computing using an amorphous FF system in a liquid aggregation state. This work poses the basis for the exploitation of a FF colloid as both an in-memory computing device and as a full-electric liquid computer thanks to its fluidity and the reported complex dynamics, via probing read-out and programmingports.

Dual Sagnac Interferometer Distributed Optical Fiber Localization Method Based on Hilbert–Huang Transform

In order to solve the problem that the dual Mach Zehnder (M-Z) interferometer system is easily affected by external environmental noise, a data signal-processing scheme based on Hilbert–Huang transform (HHT) is proposed to achieve high-precision location with distributed optical fibers. The polarization compensation module has a built-in dual Sagnac interferometer system which is used to stabilize the polarization state of the Sagnac interferometer. The eigenmode function is obtained by empirical mode decomposition of the received two optical signals, and then the Hilbert spectrum is obtained by superimposing the Hilbert transform, so that the high-similarity curve caused by the vibration signal can be clearly and intuitively extracted. The optical signal information can be calculated based on the cross-correlation and delay estimation algorithm to accurately obtain the vibration position information. The experimental results show that the positioning accuracy can reach ±11 m, with a sensing fiber length of 15 km and a sampling rate of 10 MHz. It is proven that the distributed optical fiber sensing technology based on the dual Sagnac interferometer system has high practical application value.

Development of an array pickup electromagnetic acoustic transducer and application to surface wave visualization

Visualization of surface wave based on signal and imaging processing schemes is an efficient way to enhance the detectability of ultrasonic testing for inspection of surface or near surface small defect in layered structures such as the thermal barrier coating (TBC) system. A full wave field measurement is necessary to get information for visualization of the ultrasonic wave. In this paper, a non-contact, array pickup electromagnetic acoustic transducer (EMAT) with 32 receiving coils and a phased array EMAT system are developed for efficient measurement of full information of surface wave field. Based on the multiple channel EMAT signals at different scanning position, a dynamic visualization algorithm is developed to image the propagation, reflection and scattering wave caused by defect and structure edges. The validities of the array pickup EMAT and the dynamic visualization algorithm are demonstrated by using both simulated and measured surface wave signals for a prototype array EMAT and an aluminum plate with small hole defect.

90-m/560-Mbps underwater wireless optical communication utilizing subband multiple-mode full permutation CAP combined with an SNR-weighted detector and multi-channel DFE.

In this paper, a joint signal processing scheme including a subband multiple-mode full permutation carrierless amplitude phase modulation (SMMP-CAP), signal-to-noise ratio weighted detector (SNR-WD), and multi-channel decision feedback equalizer (MC-DFE) is proposed to mitigate the bandwidth limitation of a high-speed long-reach underwater wireless optical communication (UWOC) system. Referring to the trellis coded modulation (TCM) subset division strategy, 16 quadrature amplitude modulation (QAM) mapping set is divided into four 4-QAM mapping subsets by SMMP-CAP scheme. An SNR-WD and an MC-DFE are employed to enhance the demodulation effect of this system in a fading channel. In a laboratory experiment, the minimal required received optical powers (ROPs) for data rates of 480 Mbps, 600 Mbps, and 720 Mbps, at hard-decision forward error correction (HD-FEC) threshold of 3.80 × 10-3, are -32.7 dBm, -31.3 dBm, and -25.5 dBm, respectively. Moreover, the proposed system successfully achieves a data rate of 560 Mbps in a swimming pool with a transmission distance up to 90 m and a total attenuation measured to be 54.64 dB. To the best of our knowledge, this is the first time to demonstrate a high-speed, long-distance UWOC system by employing an SMMP-CAP scheme.

Guided Wave-Based Damage Detection of Square Steel Tubes Utilizing Structure Symmetry

Square steel tube, which is widely used in civil engineering, can suffer from a wide variety of damages and aging defects, thus its nondestructive testing (NDT) has attracted wide attention. This work proposes an ultrasonic guided wave (UGW)-based damage detection method for square steel tubes using structure symmetry. Firstly, the dispersion characteristics of square steel tubes are obtained using the semi-analytical finite element (SAFE) method, after which the optimal guided wave modes for damage located on the long and short edges of the steel tube are selected by modal analysis. Then, using the symmetry of the square steel tube’s section, the symmetric layout scheme of the transmitters and the receivers is designed; on this basis, a signal processing strategy for damage detection is proposed by subtracting the receiving signals obtained from symmetric positions. Finally, the effectiveness of the proposed damage detection method is verified by numerical simulations and laboratory experiments. The results show that the proposed method has good inspection accuracy for crack and hole damages on both the long and short edges of square steel tube because the dispersion effect and clutters can be reduced utilizing structure symmetry. It is worth mentioning that the inspection effect for corner holes can be enhanced by modifying the position of the receivers.

High-quality surface wave retrieval from vibrations generated by high-speed trains moving on viaducts

Short-time passive surface wave imaging of the shallow subsurface faces great challenges due to the lack of anthropogenic noise in areas far away from towns. Vibrations generated by high-speed trains (HST) are good complements because of its strong energy and broad frequency band. The processing scheme of surface wave imaging from HST vibrations has not been systematically studied. We propose an optimized workflow of high-quality surface wave imaging from HST vibrations. An HST signal selection method is used to automatically select the data during the HST running through the stationary phase zone of the survey line. The characteristic of sharp equidistant spectral lines in the frequency spectrum of HST signals will distort the virtual shot gather and the frequency domain normalization operation can suppress the distortion. The phase weighted stacking and the multi-channel correlation weighted stacking are applied to improve the signal-to-noise ratio of the virtual shot gather. The HST signal processing scheme is applied to field data with four survey lines and surface wave signals are better retrieved than using the conventional ambient noise processing scheme. The results demonstrate the advantage of our proposed workflow in real-world applications, which provides a tool of surface wave imaging from HST vibrations.

Power-Efficient Voronoi Constellations for Fiber-Optic Communication Systems

Voronoi constellations (VCs) are considered as an effective geometric shaping method due to their high power efficiencies and low complexity. In this paper, the performance of 16- and 32-dimensional VCs with a variety of spectral efficiencies transmitted in the nonlinear fiber channel are investigated. Both single-channel and wavelength-division multiplexing systems are considered for the transmission of the VCs, as well as different signal processing schemes, including chromatic dispersion compensation and digital backpropagation. Multiple performance metrics including the uncoded bit error rate, mutual information (MI), and generalized mutual information (GMI) of VCs are evaluated. Compared with quadrature amplitude modulation (QAM) formats, the VCs provide 1.0–2.4 dB launch power gains, up to 0.50 bits/symbol/dimension-pair MI gains, up to around 30% potential reach increase at the same MI, and up to 0.30 bits/symbol/dimension-pair GMI gains in a limited launch power range. The observed performance gains over QAM are found higher than in the back-to-back case. Moreover, a general GMI estimation method for very large constellations using importance sampling is proposed for the first time.

An optoelectronic muscle contraction sensor for prosthetic hand application.

Surface electromyography (sEMG) is considered an established means for controlling prosthetic devices. sEMG suffers from serious issues such as electrical noise, motion artifact, complex acquisition circuitry, and high measuring costs because of which other techniques have gained attention. This work presents a new optoelectronic muscle (OM) sensor setup as an alternative to the EMG sensor for precise measurement of muscle activity. The sensor integrates a near-infrared light-emitting diode and phototransistor pair along with the suitable driver circuitry. The sensor measures skin surface displacement (that occurs during muscle contraction) by detecting backscattered infrared light from skeletal muscle tissue. With an appropriate signal processing scheme, the sensor was able to produce a 0-5V output proportional to the muscular contraction. The developed sensor depicted decent static and dynamic features. In detecting muscle contractions from the forearm muscles of subjects, the sensor showed good similarity with the EMG sensor. In addition, the sensor displayed higher signal-to-noise ratio values and better signal stability than the EMG sensor. Furthermore, the OM sensor setup was utilized to control the rotation of the servomotor using an appropriate control scheme. Hence, the developed sensing system can measure muscle contraction information for controlling assistive devices.

Multidimensional Signal Processing for High Areal Density Heated-Dot Magnetic Recording

In this article, a new multidimensional signal processing scheme for a heated-dot magnetic recording (HDMR) system using double-layered bit-patterned media (BPM) is proposed. This proposed signal processing scheme is capable of simultaneously detecting data sequences recorded on two tracks in each layer sequentially. The effective transmission rate of the HDMR system with two-track simultaneous log-likelihood ratio (LLR) detection and double-layered recording can be increased about four times that of the HDMR system with single-track LLR detection and single-layered recording if the data sequence recorded on each track has the same rate. It is shown that the error rate performance of the HDMR system with two-track simultaneous LLR detection and double-layered recording shows a significant improvement over the HDMR system with single-track LLR detection and single-layered recording by computer simulation.

Real-time considerations for a source-time dominant auralization scheme

A well-designed recording system can capture a moving source without risk of distortions, knowledge of the source or path, or transmission of information back to the source (i.e., a smartphone can reasonably record a plane flying overhead). This necessarily happens in real time. It would be good if signal processing schemes for auralization possessed these properties. Recent work on the NoTAP method of auralization proposed an asynchronous sample rate conversion scheme that keeps track of the (nonuniform) rate of incoming samples to formulate an effective incoming sampling frequency. This value allows the method to predict what frequency regions at the receiver are vulnerable to aliasing or imaging artifacts. Strategies of oversampling and filtering can be used to eliminate these problem regions while preserving as much of the original content as possible given the desired receiver sampling frequency. This approach creates a situation where the receiver processing can run independently of the source/path processing making it attractive for real-time implementation. This presentation discusses the challenges associated with producing a truly real-time scheme. A three-way tradeoff emerges between an interpolation mechanism that generates decorrelated noise, the computational burden, and the nearness to absolute real-time with which one wants the scheme to run.

Focusing late-time returns from elastic targets in bistatic collection geometries

Targets encountered during synthetic aperture sonar (SAS) surveys may exhibit elastic scattering behavior and re-radiate sound after initial interrogation. These re-radiated returns are often described as “late-time” energy, as they reach the sonar after the initial geometric returns. Range-specific focusing methods can enhance acoustic features such as late-time energy, but these methods typically make a monostatic sonar approximation that may not hold in very shallow water sensing geometries. This presentation will discuss the development of a late-time reconstruction algorithm applicable to bistatic sonar geometries. Using both simulated and experimental sonar data from monostatic and bistatic collection geometries, this work will first quantify the differences between traditionally beamformed imagery and late-time-focused imagery using common image quality metrics. Next, we will quantitatively compare the impact of collection geometry on the performance of late-time focusing algorithms. Finally, the work will describe methods that use information from a multi-static collection to compress late-time energy down to a high-contrast, spatiallycondensed point. The analysis of these signal processing strategies will focus on their potential applications to automatic target recognition.

Efficient Space-Time Signal Processing Scheme of Frequency Synchronization and Positioning for Sensor Networks.

The orthogonal frequency division multiple access (OFDMA) technique has been widely employed in sensor networks as the data modulation scheme. This study presents a one-dimensional (1D) space-time signal processing scheme for the joint estimation of direction of arrival (DOA) and carrier frequency offsets (CFOs) in OFDMA uplink systems. The proposed approach, initiated by a one-dimensional ESPRIT algorithm, involves estimating the DOAs of the received signal to identify subscriber positions. Spatial beamformers are then used to suppress multiple access interference and separate each subscriber's signal from the received signal. The outputs of the spatial beamformer are decimated to estimate the CFO of each subscriber. Compared with conventional two-dimensional parameter estimation algorithms, the proposed one-dimensional algorithm has a higher estimation accuracy and significantly lower computational complexity.

Low-False-Alarm-Rate Timing and Duration Estimation of Noisy Frequency Agile Signal by Image Homogeneous Detection and Morphological Signature Matching Schemes.

Frequency hopping spread spectrum (FHSS) applies widely to communication and radar systems to ensure communication information and channel signal quality by tuning frequency within a wide frequency range in a random sequence. An efficient signal processing scheme to resolve the timing and duration signature from an FHSS signal provides crucial information for signal detection and radio band management purposes. In this research, hopping time was first identified by a two-dimensional temporal correlation function (TCF). The timing information was shown at TCF phase discontinuities. To enhance and resolve the timing signature of TCF in a noisy environment, three stages of signature enhancement and morphological matching processes were applied: first, computing the TCF of the FHSS signal and enhancing discontinuities via wavelet transform; second, a dual-diagonal edge finding scheme to extract the timing pattern signature and eliminate mismatching distortion morphologically; finally, Hough transform resolved the agile frequency timing from purified line segments. A grand-scale Monte Carlo simulation of the FHSS signals with additive white Gaussian noise was carried out in the research. The results demonstrated reliable hopping time estimation obtained in SNR at 0 dB and above, with a minimal false detection rate of 1.79%, while the prior related research had an unattended false detection rate of up to 35.29% in such a noisy environment.

Structural displacement monitoring using ground-based synthetic aperture radar

This study develops a ground-based synthetic aperture radar (GBSAR) imaging system and interferometric processing framework for structural health monitoring (SHM). Radar remote sensing for displacement monitoring plays a vital role in SHM. Radar sensors and, more specifically, GBSAR systems have gained more attention in recent studies due to their capability to overcome the limitations of other contact or non-contact SHM sensors. This paper proposes a three-dimensional SAR imaging system and advanced signal processing scheme to extract continuous (fast) displacement components, such as structural vibrations, and discontinuous (slow) displacements, such as subsidence or uplift, using SAR time-series datasets. Using controlled experiments, this study shows that the developed GBSAR can monitor sub-millimeter displacements with high spatial resolution and 0.02 mm precision in the LOS direction. Moreover, several simulations are carried out to evaluate the proposed displacement monitoring algorithms. Accordingly, the proposed continuous monitoring framework can measure fast LOS displacements with better than 0.03 mm precision by reducing the effects of radar movement, clutters, and disturbances. Also, evaluations on a simulated monitoring scene at 20 m from the GBSAR’s LOS show that the proposed discontinuous displacement monitoring algorithm can estimate 3D displacement vectors with sub-millimeter precision. The results show that the developed GBSAR can be used for repeat-pass LOS displacement monitoring and the proposed algorithms demonstrate high potential for measuring continuous sub-second LOS displacements and long-term 3D displacement vectors.