Cross-correlation Processing Research Articles

Speech enhancement and encoding by combining SS-VAD and LPC

In this paper, the encoding of noisy and enhanced speech data is demonstrated. To encode and enhance the speech data under an uncontrolled environment, the linear predictive coding (LPC) and spectral subtraction with voice activity detection (SS-VAD) methods are studied individually. The noisy speech data is obtained by considering the amalgamation of the clean speech signal and noise model and it is encoded using the LPC technique. The LPC uses a lossy compression procedure to encode the speech data which converts the data rate from 64 to 2.4 Kbps. Due to reverberations and degradations in noisy speech data, the quality of encoded noisy speech data is very less. Therefore, an algorithm is proposed to enhance and encode the speech data by combining SS-VAD and LPC under degraded conditions. In the first step, the encoding of noisy speech data is done using LPC and its performance is evaluated using signal-to-ratio. The noisy speech data is given as input to the SS-VAD algorithm and the output of SS-VAD is given as input to the LPC encoder is followed in the second step. In the LPC encoder, the coefficients are extracted from the input speech data to design all-pole filters. The cross correlation process is also done for differentiating the voiced and unvoiced samples at the analysis step. The pitch information and extracted coefficients are used in the synthesis step. The experiments are conducted for different types of noisy speech data which are degraded by musical noise, F16 noise, factory noise, and car noise. The experimental results show that there is a significant improvement in the quality of enhanced encoded speech data obtained by the proposed method compared to encoded noisy speech data. The schematic representation of outputs of LPC and proposed combined SS-VAD and LPC waveforms are also given in this work.

Joint Cramér-Rao Lower Bound for Nonlinear Parametric Systems With Cross-Correlated Noises

Joint state and parameter estimation (JSPE) has a surge of interest due to its dual purposes in many fields, such as sensor registration and signal processing. In this letter, a recursive joint Cramer-Rao lower bound (JCRLB) is developed for JSPE of nonlinear parametric systems with cross-correlated process and measurement noises at the same time. The JCRLBs for two special cases of such systems with additive Gaussian noises are also studied. Illustrative examples show the effectiveness of the JCRLB for the performance evaluation of JSPE of nonlinear parametric systems with cross-correlated noises at the same time.

ОСОБЛИВОСТІ ОБРОБКИ ТА ОЦІНЮВАННЯ ВЗАЄМНОЇ ЗАТРИМКИ ВИПАДКОВИХ ШИРОКОСМУГОВИХ СИГНАЛІВ НА ТЛІ НЕГАУСОВИХ ЗАВАД

Peculiarities of operation conditions of methods and tools for assessing delay and angular position of the source of a random wideband signal when it is received by two spatially displaced sensors are analyzed. Special attention is paid to modeling of possible non-Gaussian noise and analyzing its effect on estimation results. It is assumed that digital processing of received signals is carried out in intervals of certain duration (parts of a second). The first feature is that, unlike many other applications of cross-correlation processing of received broadband signals or their analogs, the information component is characterized by possible nonstationarity both in terms of power and, accordingly, the signal-to-noise ratio, and spectral composition of oscillations. The second feature is that both due to possible low signal-to-noise ratios in some areas, and as a result of non-Gaussian noise, that usually has a distribution with heavy tails, abnormal estimates of the delay, and angular position of a source are possible. In such situations, it is desirable to apply a method for estimating the delay of random broadband signals, which will be robust to non-Gaussian noise and exclude abnormal estimates or at least to the maximum extent reduce the probability of their occurrence. The purpose of this work is to study the possibilities of using other measures of similarity and analysis of processing efficiency. It is shown that this can be achieved due to the use of methods based on the calculation of robust distances. The efficiency of various modifications of the proposed method is shown depending on the intensity and impulsivity of the noise. Following various criteria, the efficiency of processing is assessed and the need for automatic obtaining of information about the noise characteristics is shown. The studies are carried out using a test wideband signal. The tasks that must be solved first of all to ensure a high efficiency of processing are formulated. The results obtained in the simulation process can be used in many technical fields, where the processing of the received signal in hard noise conditions is kept.

Signal Processing for Parametric Acoustic Sources Applied to Underwater Communication.

For years, in the field of underwater acoustics, a line of research with special relevance for applications of environmental monitoring and maritime security has been developed that explores the possibilities of non-linear phenomena of sound propagation, especially referring to the so-called parametric effect or self-modulation. This article shows the results of using a new modulation technique based on sine-sweep signals, compared to classical modulations (FSK and PSK). For each of these modulations, a series of 16-bit strings of information with different frequencies and durations have been performed, with the same 200 kHz carrier wave. All of them have been tested in the Hydroacoustic Laboratory of the CTN and, through the application of cross-correlation processing, the limitations and improvements of this novel processing technique have been evaluated. This allows reaching better limits in discrimination of bits and signal-to-noise ratio used in underwater parametric acoustic communications.

Classification of ST segment in ECG signals based on cross correlated supervised data

This paper describes an automated selection of the ST segment in 12 leads electrocardiogram (ECG) as well as its classification based on cross correlation. Our proposed method classifies five categories of ST segment which are (a) Up slop (b) Down slop (c) Horizontal (Normal) (d) Concave (e) Convex using cross correlation process. We compare the main ECG (patient ECG) ST segment with the above-mentioned reference ST segments. In this work we have used MIT-BIH ST change database and European ST-T change database where every database contains minimum 30 min and maximum 1-h episode. Our method contains the following steps (1) Filtering ECG signal and Detrending it (2) R peak and S peak detection (3) Starting and ending point detection of ST segment (4) Comparing with ST segment supervised data (5) Classifying the ST segment. We have used total 1,34,879 beats where 58,331 beats from MIT-BIH ST change database and 74,609 beats from European ST-T change database. We have correctly selected total 126,608 ST segments. ST segment classification accuracy is 88.20% for MIT-BIH ST change database and 96.18% for European ST-T change database. The method confirms satisfactory performance with an overall accuracy of 92.1% which is helpful to the detection of major heart diseases like myocardial ischemia.

A note on power-law cross-correlated processes

Abstract In this paper, some mathematical support is provided to properly justify the validity of the so-called multifractal height cross-correlation analysis (MFHXA), first contributed by Kristoufek (2011)[1]. With this aim, we extend several concepts from univariate random functions and their increments to the bivariate case. Specifically, we introduce the bivariate cumulative range as well as the concepts of co-self-similar processes and random processes with co-affine increments of bivariate parameter. They allow us to introduce a new procedure, named multifractal cross-correlated fractal dimension (MFXFD) algorithm. We theoretically prove the validity of such a novel approach to calculate the bivariate Hurst exponent of a pair of processes with co-affine increments. Interestingly, that class of random functions is characterised theoretically in terms of co-self-similar processes. Moreover, we prove that a pair of univariate self-similar processes are co-self-similar and their bivariate Hurst exponent coincides with the mean of their univariate parameters. Finally, we test the behavior of the new algorithm to calculate the bivariate Hurst exponent of a pair of time series. Both DCCA and MFHXA procedures are involved in such an empirical comparison. Our results suggest that the new MFXFD performs (at least) as well as the other approaches with shorter deviations with respect to the mean of the bivariate Hurst exponents.

Assessing Site-Specific Enhancements Imparted by Hyperpolarized Water in Folded and Unfolded Proteins by 2D HMQC NMR.

Hyperpolarized water can be a valuable aid in protein NMR, leading to amide group 1H polarizations that are orders of magnitude larger than their thermal counterparts. Suitable procedures can exploit this to deliver 2D 1H–15N correlations with good resolution and enhanced sensitivity. These enhancements depend on the exchange rates between the amides and the water, thereby yielding diagnostic information about solvent accessibility. This study applied this “HyperW” method to four proteins exhibiting a gamut of exchange behaviors: PhoA(350–471), an unfolded 122-residue fragment; barstar, a fully folded ribonuclease inhibitor; R17, a 13.3 kDa system possessing folded and unfolded forms under slow interconversion; and drkN SH3, a protein domain whose folded and unfolded forms interchange rapidly and with temperature-dependent population ratios. For PhoA4(350–471) HyperW sensitivity enhancements were ≥300×, as expected for an unfolded protein sequence. Though fully folded, barstar also exhibited substantial enhancements; these, however, were not uniform and, according to CLEANEX experiments, reflected the solvent-exposed residues. R17 showed the expected superposition of ≥100-fold enhancements for its unfolded form, coexisting with more modest enhancements for their folded counterparts. Unexpected, however, was the behavior of drkN SH3, for which HyperW enhanced the unfolded but, surprisingly, enhanced even more certain folded protein sites. These preferential enhancements were repeatedly and reproducibly observed. A number of explanations—including three-site exchange magnetization transfers between water and the unfolded and folded states; cross-correlated relaxation processes from hyperpolarized “structural” waters and labile side-chain protons; and the possibility that faster solvent exchange rates characterize certain folded sites over their unfolded counterparts—are considered to account for them.

Acoustic emission propagation characteristics and damage source localization of asphalt mixtures

Fracture of asphalt materials has been a critical issue that affects the fatigue performance and service life of asphalt pavements. Acoustic emission (AE) technique, as a kind of non-destructive testing (NDT) method, can effectively detect minor damage in various materials. The objective of this paper was to propose a damage source localization method suitable for understanding the fracture behavior of asphalt mixtures by AE detection. Firstly, the pencil-lead-break (PLB) tests were conducted on asphalt mixture beams to explore the propagation characteristics of AE signals, and a reasonable layout scheme of AE sensors was determined for monitoring the AE process of asphalt mixtures. Secondly, the wavelet threshold denoising method was utilized to extract effective information from AE signals associated with the pencil-lead breaks on the surface of asphalt mixture beam by simultaneously considering the wavelet basis functions, decomposition levels and threshold rules. Finally, an effective time difference of arrival (TDOA) estimation method combining noise reduction, wavelet decomposition and cross-correlation processing was established to accurately locate the damage source of asphalt mixtures. The results show that there is less serious attenuation of amplitude and energy of AE parameters and frequency spectrum of AE waveforms within the range of 100 mm in asphalt mixtures. The larger signal-to-noise ratio (SNR) and the smaller root mean square error (RMSE) of denoised AE signals indicate that the threshold denoising method optimized by the Fruit Fly Optimization Algorithm (FOA) is more effective for AE detection of asphalt mixtures. The improved TDOA estimation method could obtain a minimum TDOA value, and the calculated locations of AE events are closer to the actual PLB points.

Inversion of head waves in ocean acoustic ambient noise.

The virtual head wave is produced through cross-correlation processing of signals containing the real, acoustic head wave. The virtual head wave has the same phase speed as the head wave, but the travel time is offset, thus the term virtual. The virtual head wave, like the real head wave, propagates in a direction corresponding to the seabed critical angle. The virtual head wave travel time varies with array depth and water column depth. However, in a refracting environment, the travel time is also dependent on the depth-dependent sound speed profile. Previously, the virtual head wave was shown as observable from measurements of ocean ambient noise, and the arrival angle was used to estimate the seabed sound speed. By also using the virtual head wave travel times, it is possible to invert for array depth and water column depth. The previous analysis was limited to the assumption of a Pekeris waveguide, which is a special case of the more realistic refracting waveguide. In this paper, the virtual head wave and the inversion method are considered in environments having refracting sound speeds. The theoretical framework and the inversion method are presented along with illustrative simulations and application to the Boundary'03 data.

Analysis of Vibration and Acoustic Signals for Noncontact Measurement of Engine Rotation Speed.

The non-contact measurement of engine speed can be realized by analyzing engine vibration frequency. However, the vibration signal is distorted by harmonics and noise in the measurement. This paper presents a novel method for the measurement of engine rotation speed by using the cross-correlation of vibration and acoustic signals. This method can enhance the same frequency components in engine vibration and acoustic signal. After cross-correlation processing, the energy centrobaric correction method is applied to estimate the accurate frequency of the engine’s vibration. This method can be implemented with a low-cost embedded system estimating the cross-correlation. Test results showed that this method outperformed the traditional vibration-based measurement method.

A Coherent Method for Simulating Active and Passive Radar Sounding of the Jovian Icy Moons

The possibility to apply passive radar sounding techniques to the Jovian icy moons, making use of Jupiter's strong decametric emissions (DAMs), has recently garnered large research interest. In this article, we propose a radar sounding simulation approach being able to simulate and compare passive and active acquisitions for a given scenario. The proposed simulator is based on the Stratton-Chu integral used with the linear phase approximation on triangular facets. The external field is modeled with plane waves, the direction, polarization, and amplitude of which can be freely chosen. The time-domain dependence can be either synthetically generated (e.g., Gaussian white noise) or taken from experimental measurements (e.g., waveforms recorded by a radio telescope observing Jupiter). For passive sounding, both autocorrelation and cross-correlation processing are considered. Validation tests were conducted on a series of ideal digital elevation models (DEMs), such as flat surfaces and subsurfaces, or Gaussian rough surfaces, and a good agreement with the existing literature was obtained. To illustrate the capabilities of the proposed simulator, we conducted additional more realistic experiments of radar sounding simulations, where we use both white noise and Jovian waveforms recorded by the LWA1 radio telescope.

Video Recording of an Air Blast Wave Resulting from Initiation of a Light-Sensitive Explosive Composition

This paper presents experimental data on the parameters of an air blast wave resulting from initiation of VS-2 light-sensitive composition by laser diode radiation. The propagation of the air blast wave front was recorded by the background-oriented schlieren method. The air blast wave front was visualized using cross-correlation processing. Empirical dependences characterizing the propagation of the air blast wave front resulting from initiation of a light-sensitive composition of arbitrary weight. Experiments confirmed the possibility of initiating VS-2 light-sensitive composition using an EV-15 electric igniter.

Ambient noise tomography of the southern sector of the Cantabrian Mountains, NW Spain

SUMMARYThis study presents the first detailed analysis of ambient noise tomography in an area of the continental upper crust in the Cantabrian Mountains (NW Spain), where a confluence of crustal scale faults occurs at depth. Ambient noise data from two different seismic networks have been analysed. In one side, a 10-short-period station network was set recording continuously for 19 months. A second set of data from 13 broad-band stations was used to extend at depth the models. The phase cross-correlation processing technique was used to compute in total more than 34 000 cross-correlations from 123 station pairs. The empirical Green's functions were obtained by applying the time–frequency, phase-weighted stacking methodology and provided the emergence of Rayleigh waves. After measuring group velocities, Rayleigh-wave group velocity tomographic maps were computed at different periods and then they were inverted in order to calculate S-wave velocities as a function of depth, reaching the first 12 km of the crust.The results show that shallow velocity patterns are dominated by geological features that can be observed at the surface, particularly bedding and/or lithology and fracturing associated with faults. In contrast, velocity patterns below 4 km depth seem to be segmented by large structures, which show a velocity reduction along fault zones. The best example is the visualization in the tomography of the frontal thrust of the Cantabrian Mountains at depth, which places higher velocity Palaeozoic rocks over Cenozoic sediments of the foreland Duero basin. One of the major findings in the tomographic images is the reduction of seismic velocities above the area in the crust where one seismicity cluster is nucleated within the otherwise quiet seismic area of the range. The noise tomography reveals itself as a valuable technique to identify shear zones associated with crustal scale fractures and hence, lower strain areas favourable to seismicity.

A Novel Monitoring Approach for Train Tracking and Incursion Detection in Underground Structures Based on Ultra-Weak FBG Sensing Array.

Tracking operating trains and identifying illegal intruders are two important and critical issues in subway safety management. One challenge is to find a reliable methodology that would enable these two needs to be addressed with high sensitivity and spatial resolution over a long-distance range. This paper proposes a novel monitoring approach based on distributed vibration, which is suitable for both train tracking and incursion detection. For an actual subway system, ultra-weak fiber Bragg grating (FBG) sensing technology was applied to collect the distributed vibration responses from moving trains and intruders. The monitoring data from the subway operation stage were directly utilized to evaluate the feasibility of the proposed method for tracking trains. Moreover, a field simulation experiment was performed to validate the possibility of detecting human intrusion. The results showed that the diagonal signal pattern in the distributed vibration response can be used to reveal the location and speed of the moving loads (e.g., train and intruders). Other train parameters, such as length and the number of compartments, can also be obtained from the vibration responses through cross-correlation and envelope processing. Experimental results in the time and frequency domains within the selected intrusion range indicated that the proposed method can distinguish designed intrusion cases in terms of strength and mode.

Image Classification for Automated Image Cross-Correlation Applications in the Geosciences

In Earth Science, image cross-correlation (ICC) can be used to identify the evolution of active processes. However, this technology can be ineffective, because it is sometimes difficult to visualize certain phenomena, and surface roughness can cause shadows. In such instances, manual image selection is required to select images that are suitably illuminated, and in which visibility is adequate. This impedes the development of an autonomous system applied to ICC in monitoring applications. In this paper, the uncertainty introduced by the presence of shadows is quantitatively analysed, and a method suitable for ICC applications is proposed: The method automatically selects images, and is based on a supervised classification of images using the support vector machine. According to visual and illumination conditions, the images are divided into three classes: (i) No visibility, (ii) direct illumination and (iii) diffuse illumination. Images belonging to the diffuse illumination class are used in cross-correlation processing. Finally, an operative procedure is presented for applying the automated ICC processing chain in geoscience monitoring applications.

A 1-GHz 64-Channel Cross-Correlation System for Real-Time Interferometric Aperture Synthesis Imaging.

We present a 64-channel 1-bit/2-level cross-correlation system for a passive millimeter wave imager used for indoor human body security screening. Sixty-four commercial comparators are used to perform 1-bit analog-to-digital conversion, and a Field Programmable Gate Array (FPGA) is used to perform the cross-correlation processing. This system can handle 2016 cross-correlations at the sample frequency of 1GHz, and its power consumption is 48.75 W. The data readout interface makes it possible to read earlier data while simultaneously performing the next correlation when imaging at video rate. The longest integration time is up to 68.7 s, which can satisfy the requirements of video rate imaging and system calibration. The measured crosstalk between neighboring channels is less than 0.068%, and the stability is longer than 10 s. A correlation efficiency greater than 96% is achieved for input signal levels greater than −25 dBm.

Micro-Doppler Ambiguity Resolution With Variable Shrinkage Ratio Based on Time-Delayed Cross Correlation Processing for Wideband Radar

Vibration or rotation on a target or any structure of a target might induce a frequency modulation on the returned radar signal, which is called micro-Doppler effect, and is widely used for many of the remote sensing applications such as target detection, classification, and recognition. However, the micro-Doppler frequency could be large and it may cause micro-Doppler ambiguities which are undesirable in these applications. In this paper, we propose a novel and flexible method to resolve the micro-Doppler ambiguities based on the time-delayed cross correlation processing of wideband radar echoes for range-spread targets. Variable-sized shrinkage ratio can be obtained to reduce the micro-Doppler frequency of the signal to an appropriate numerical value, and the micro-Doppler ambiguities can be resolved in different situations. The effectiveness of the proposed method is validated by simulations and real data experiments.

A study on the ambient noise field at a hydroacoustic array near Robinson Crusoe Island

Continuous long-term sound sources are recorded at hydroacoustic station H03S, a threeelement hydrophone array south of Robinson Crusoe Island between 2014 April 23 and 2017 August 20. The origin of the signal between 3 and 20 Hz is investigated by using cross-correlation, array processing using plane wave beamforming and spectral analysis. Onebit normalization is successfully applied as a cross-correlation pre-processing step in order to suppress undesired earthquake events in the data. Traveltimes retrieved from averaged cross-correlations do not yield a coherent array direction of arrival. Averaged envelopes of the cross-correlations, however, indicate a coherent signal approaching H03S from a south. southwest direction. Beamforming indicates two dominant backazimuth directions: 172°-224° (Antarctica) and 242° (Monowai Volcanic Seamount). This continuous source field creates possibilities to investigate the applicability of acoustic thermometry at hydrophones H03 S1. S2. Cross-correlation and array processing indicate significant directional variation in local propagation, most likely related to the steep slope in the bathymetry near H03S. In addition, it is demonstrated that the ambient noise field is not sufficiently equipartitioned. It is shown that this causes a large error in the estimated temperature, primarily due to the short receiver spacing. These large errors have not been addressed in previous studies on deep-ocean acoustic thermometry. Hence, it is shown that acoustic thermometry does not perform well on small arrays such as H03S. The power spectral density yields a strong broadband signal in January. March, most likely related to iceberg noise. A narrow banded signal around 17 Hz between April and September corresponds to whale calls. The best-beam sound pressure levels towards Antarctica are compared to ERA5 climatologies for sea ice cover and normalized stress into the ocean, supporting the hypothesis of iceberg noise.

TDOA estimation of dual-satellites interference localization based on blind separation

The time difference of arrival (TDOA) estimation plays a crucial role in the accurate localization of the satellite interference source. In the dual-satellites interference source localization system, the target signal from the adjacent satellite is likely to be interfered by the normal communication signal with the same frequency. Therefore, the signal to noise ratio (SNR) of the target signal would become too low, and the TDOA estimation through cross-correlation processing would be unreliable or even unattainable. This paper proposes a technique based on blind separation to solve the co-channel interference problem, where separation of the mixed signal can be carried out by the particle filter (PF) algorithm. The experimental results show that the proposed method could achieve more accurate TDOA estimation. The measured data obtained by using the software radio platform at 915 MHz and 2 GHz respectively verify the effectiveness of the proposed method.

Maximum Likelihood Delay and Doppler Estimation for Passive Sensing

We consider the problem of delay and Doppler frequency estimation of a moving target in passive radar using a non-cooperative illuminator of opportunity (IO). The passive radar consists of a reference channel (RC), i.e., an antenna steered to the IO, and a surveillance channel (SC) that collects target echoes. We examine the maximum-likelihood estimator (MLE) for the passive estimation problem by modeling the unknown IO waveform as a deterministic process. Under this condition, the passive MLE is shown to reduce to a cross-correlation and search process using the surveillance signal and a delay-Doppler compensated version of the reference signal. We present two implementations for the passive MLE, including a direct and, respectively, a fast implementation based on a two-dimensional Fast Fourier Transform. In addition, the Cramer-Rao Bound is derived to benchmark the passive estimation performance. The passive MLE is compared via numerical simulation with its active counterpart, which has the exact knowledge of the waveform and uses it for cross-correlation. Our results show that the signal-to-noise ratio (SNR) in the RC relative to the SNR in the SC has a significant impact on the passive MLE. Specifically, if the former is notably higher than the latter (by, e.g., 5 dB), there is a minor difference between the passive and active MLEs for the delay and Doppler estimation; otherwise, the difference is non-negligible and increases with the SNR.