Cross-correlation Detection Research Articles

Signal Acquisition and Algorithm Design for Bioimpedance-Based Heart Rate Estimation from the Wrist

Background: Heart rate (HR) is a critical biomarker that provides insights into overall health, stress levels, and the autonomic nervous system. Pulse wave signals contain valuable information about the cardiovascular system and heart status. However, signal acquisition in wearables poses challenges, particularly when using electrical sensors, due to factors like the distance from the heart, body movement, and suboptimal electrode placement. Methods: Electrical bioimpedance (EBI) measurements using bipolar and tetrapolar electrode systems were employed for pulse wave signal acquisition from the wrist in both perpendicular and distal configurations. Signal preprocessing techniques, including baseline removal via Hankel matrix methods, normalization, cross-correlation, and peak detection, were applied to improve signal quality. This study describes the combination of sensor-level signal acquisition and processing for accurate wearable HR estimation. Results: The bipolar system was shown to produce larger ΔZ(t), while the tetrapolar system demonstrated higher sensitivity. Distal placement of the electrodes yielded greater ΔZ(t) (up to 0.231 Ω) when targeting both wrist arteries. Bandpass filtering resulted in a better signal-to-noise ratio (SNR), achieving 3.6 dB for the best bipolar setup and 4.8 dB for the tetrapolar setup, compared to 2.6 and 3.3 dB SNR, respectively, with the Savitzky–Golay filter. The custom HR estimation algorithm presented in this paper demonstrated improved accuracy over a reference method, achieving an average error of 1.8 beats per minute for the best bipolar setup, with a mean absolute percentage error (MAPE) of 8%. Conclusions: The analysis supports the feasibility of using bipolar electrode setups on the wrist and highlights the importance of electrode positioning relative to the arteries. The proposed signal processing method, featuring a preprocessing pipeline and HR estimation algorithm, provides a proof-of-concept demonstration for HR estimation from EBI signals acquired at the wrist.

Optimising spectroscopic observations of transiting exoplanets

Context. When observing the atmospheres of transiting exoplanets using high-resolution spectroscopy, the aim is to detect well-resolved spectral features with high signal-to-noise ratios (S/Ns), as is possible today with modern spectrographs. However, obtaining such high-quality observations comes with a trade-off: a lower cadence of fewer, longer exposures across the transit collects more photons thanks to reduced overheads, enhancing the S/N of each observation, while a higher cadence of several shorter exposures minimises spectral feature smearing due to the continuously changing radial velocity of the planet. Aims. Considering that maximising S/N and minimising smearing are both beneficial to analysis, there is a need to identify the optimal compromise between the two for a given target. In this work, we aim to establish where this compromise lies for a typical exoplanet transit observation in order to benefit future data collection and subsequent interpretation. Methods. We modelled real transit events based on targets as they would be observed with VLT/CRIRES+ at Paranal Observatory, Chile. Creating four hypothetical scenarios, we simulated each set of transmission spectra across 100 realisations of the same transit event in order to vary the time resolution only. We removed telluric and stellar lines from these data sets using the SYSREM algorithm and analysed them through cross-correlation with model templates, measuring how successfully each time resolution and case detected the planetary signal and exploring how the results vary. Results. We demonstrate that there is a continuous change in the significance of the cross-correlation detection based on the trade-off between high and low time resolutions, and that, averaged over a large number of realisations, the function of this significance has clear maxima. The strength and location of these maxima vary depending on, for example, planet system parameters, instrumentation, and the number of removal iterations. We discuss why observers should therefore take several factors into account using a strategy akin to the ‘exposure triangle’ employed in traditional photography where a balance must be struck by considering the full context of the observation. Our method is robust and may be employed by observers to estimate the best observational strategies for other targets.

Keck Planet Imager and Characterizer Emission Spectroscopy of WASP-33b

We present Keck Planet Imager and Characterizer (KPIC) high-resolution (R ∼35,000) K-band thermal emission spectroscopy of the ultrahot Jupiter WASP-33b. The use of KPIC’s single-mode fibers greatly improves both blaze and line-spread stabilities relative to slit spectrographs, enhancing the cross-correlation detection strength. We retrieve the dayside emission spectrum with a nested-sampling pipeline, which fits for orbital parameters, the atmospheric pressure–temperature profile, and the molecular abundances. We strongly detect the thermally inverted dayside and measure mass-mixing ratios for CO (), H2O (), and OH (), suggesting near-complete dayside photodissociation of H2O. The retrieved abundances suggest a carbon- and possibly metal-enriched atmosphere, with a gas-phase C/O ratio of , consistent with the accretion of high-metallicity gas near the CO2 snow line and post-disk migration or with accretion between the soot and H2O snow lines. We also find tentative evidence for 12CO/13CO ∼ 50, consistent with values expected in protoplanetary disks, as well as tentative evidence for a metal-enriched atmosphere (2–15 × solar). These observations demonstrate KPIC’s ability to characterize close-in planets and the utility of KPIC’s improved instrumental stability for cross-correlation techniques.

Cardinality increasing of SAC-OCDMA system using novel decoder design

Abstract The large number of active users that optical code-division multiple access (OCDMA) offers makes it an attractive technology choice. OCDMA loses its noise immunity due to non-ideal correlation since the maximum auto-correlation and minimum cross-correlation detection technique is required in OCDMA systems. There are several detection techniques like complementary detection, direct detection, etc. This paper presents a new detection technique that is particularly suited for SAC-OCDAM systems with FCZ codes. The simulation results showed that by overcoming the effects of the MAI, significant performance improvements can be achieved.

Detection of GPS C/A Code Self-Interference: Monitor Overview and Applicability

<h3>Abstract</h3> Self-interference can cause large errors of up to tens of meters on the GPS C/A code pseudorange measurement. Although the probability of an occurrence of large self-interference errors is small, to enable the use of C/A code phase measurements in high accuracy or safety-of-life applications, a detection or mitigation method is needed. A stressful case of self-interference is modeled on a GPS hardware simulator to investigate monitor performance using real signal results. A summary of contributions in this paper follows. Self-interference pseudorange error characteristics within and mitigation requirements for the Ground Based Augmentation System (GBAS) Approach Service Type D (GAST-D) environment are identified. Existing monitors are evaluated for their response to self-interference and their ability to detect the error based on the GAST-D environment. This includes the potential for misidentification of the error. A novel Frequency Domain Cross-Correlation (FDCC) detector is proposed that can uniquely identify self-interference error with no siting constraints.

Microbubble Identification Based on Decision Theory for Ultrasound Localization Microscopy

Ultrasound localization microscopy (ULM) enables the evaluation of the vascular microstructure by detecting, localizing, and tracking microbubbles (MBs) in the vascular network. ULM provides a vascular map of the network with improved spatial resolution but with an acquisition time of several minutes. Thus, it is of great importance to increase the number of MBs detected in order to limit the acquisition time. The standard MB detection method in ULM assumes that the contrast agents are the highest-intensity structures on the ultrasound images. However, in vivo data show that MB intensity may be lower than residual tissue or even noise. Thus, to facilitate the detection of these MBs, an MB detector based on decision theory is proposed in this paper. In this study, the proposed method based on the Neyman–Pearson criterion is compared with the standard intensity-based and the normalized cross-correlation detection methods on simulated and in vivo rat brain and kidney data. The new detection method makes it possible to control the false positive detection rate without degrading the MB detection rate on simulated data, to enhance the ULM vessel map resolution on in vivo brain data and to detect more vessels on in vivo kidney data.

Synchronization of the internal dynamics of optical soliton molecules

Compact bound states of light pulses in ultrafast lasers are known as optical soliton molecules. They constitute nonlinear superstructures of choice to investigate complex dynamical phenomena that manifest similarly in a wide range of nonlinear systems. Akin to matter molecules, optical soliton molecules can feature vibrational motions between their internal constituents. However, these vibrations are intrinsically nonlinear, with oscillation frequencies sensitive to system parameters. Therefore, vibrating soliton molecules present an opportunity for control. We here investigate the precise control of their oscillation frequencies through the universal mechanism of synchronization between master and slave oscillators. Self-oscillating soliton molecules are prepared within a passively mode-locked fiber laser. We experimentally demonstrate the synchronization of the internal vibrations of soliton molecules through the optical injection of a master oscillator signal. Direct observation of the synchronization process is enabled by balanced optical cross-correlation detection, a technique allowing real-time detection of intramolecular separation with femtosecond temporal resolution. We show efficient sub-harmonic, fundamental, and super-harmonic synchronization, forming a pattern of Arnold tongues with respect to the injection strength. Numerical simulations support experimental observations. By retrieving these universal synchronization features, the role of the soliton molecule as a nonlinear dynamical system of chief importance is further highlighted.

Doppler-Spread Targets Detection for FMCW Radar Using Concurrent RDMs

An amplitude weighted cross-correlation detector is proposed for the detection of the Doppler-spread target (DST), based on the frequency modulated continuous waveform (FMCW) radar. The concurrent range-Doppler matrices (RDM) make cross-correlation optimized with higher accumulation gain and significantly reduced computation effort. A novel measurement of signal sparseness is defined. The quantitative analysis of the proposed detector, compared with the energy integration detector, is realized based on the signal sparseness. Two generalizations of proposed detector are discussed for the number of antennas greater than two. Data from a walking pedestrian are got and used to verify the effectiveness of the proposed detector.

Transmission spectroscopy of the ultra-hot Jupiter MASCARA-4 b

Context. Ultra-hot Jupiters (UHJs), rendering the hottest planetary atmospheres, offer great opportunities of detailed characterisation with high-resolution spectroscopy. MASCARA-4 b is a recently discovered close-in gas giant belonging to this category. Aims. We aim to characterise MASCARA-4 b, search for chemical species in its atmosphere, and put these in the context of the growing knowledge on the atmospheric properties of UHJs. Methods. In order to refine system and planet parameters, we carried out radial velocity measurements and transit photometry with the CORALIE spectrograph and EulerCam at the Swiss 1.2 m Euler telescope. We observed two transits of MASCARA-4 b with the high-resolution spectrograph ESPRESSO at ESO’s Very Large Telescope. We searched for atomic, ionic, and molecular species via individual absorption lines and cross-correlation techniques. These results are compared to literature studies on UHJs characterised to date. Results. With CORALIE and EulerCam observations, we update the mass of MASCARA-4 b (Mp = 1.675 ± 0.241 MJup) as well as other system and planet parameters. In the transmission spectrum derived from ESPRESSO observations, we resolve excess absorption by Hα, Hβ, NaI D1&amp;D2, CaII H&amp;K, and a few strong lines of MgI, FeI, and FeII. We also present the cross-correlation detection of Mg I, CaI, Cr I, Fe I, and Fe II. The absorption strength of Fe II significantly exceeds the prediction from a hydrostatic atmospheric model, as commonly observed in other UHJs. We attribute this to the presence of Fe II in the exosphere due to hydrodynamic outflows. This is further supported by the positive correlation of absorption strengths of Fe II with the Hα line, which is expected to probe the extended upper atmosphere and the mass loss process. Comparing transmission signatures of various species in the UHJ population allows us to disentangle the hydrostatic regime (as traced via the absorption by Mg I and Fe I) from the exospheres (as probed by Hα and Fe II) of the strongly irradiated atmospheres.

Cross-correlations between mm-wave line-intensity mapping and weak-lensing surveys: preliminary consideration of long-term prospects

ABSTRACT The field of millimetre-wave line-intensity mapping (LIM) is seeing increased experimental activity with pathfinder surveys already deployed or deploying in the next few years, making spectroscopic measurements of unresolved atomic and molecular line emission tracing the large-scale structure of the Universe. The next decade will also see the Rubin Observatory Legacy Survey of Space and Time (LSST) undertake a photometric galaxy survey programme of unprecedented scope, including measurements of cosmic shear exploiting weak gravitational lensing (WL) of background galaxies to map projected large-scale structure. We consider prospects for detecting angular cross-power spectra between non-tomographic cosmic shear and mm-wave LIM surveys that measure emission from CO lines at z = 0.5–1. We forecast that once the LSST Year 10 WL data set is available, a future LIM experiment, conceivably deployed in the next 10–15 yr, would enable such a cross-correlation detection with an overall signal-to-noise ratio of 50, although the current pathfinder generation of CO/[C ii] surveys are more likely to achieve a marginal 2σ detection against an earlier-stage LSST WL data set. The signal has modest astrophysical constraining power yielding competitive constraints on cosmic molecular gas density at z ≲ 1, and degeneracies between astrophysical parameters and the intrinsic alignment amplitude mean that external information on either one could allow the cross-correlation analysis to significantly improve its constraints on the other.

DrumCorr program for selecting volcanic earthquake multiplets based on cross-correlation analysis

The DrumCorr program based on cross-correlation detection has been developed to identify multiplets of the volcanic earthquakes. The program is implemented in Python 3 and reads ASCII and MiniSEED seismic data formats. The article presents the algorithm of the program, describing the cross-correlation detector and an example of subsequent processing of seismic data. The program was applied to volcanic earthquakes of the «drumbeats» seismic regime and allowed to identify earthquake multiplets characterized by various wave forms. The article presents the algorithm of the program, describing the cross-correlation detector, the features of the weak volcanic earthquakes selection by the STA/LTA method. And the primary analysis of the values of the correlation coefficients with the calculation of their standard errors depending on different signal-to-noise ratios.

Analysing the Impact of Large Data Imports in OpenStreetMap

OpenStreetMap (OSM) is a global mapping project which generates free geographical information through a community of volunteers. OSM is used in a variety of applications and for research purposes. However, it is also possible to import external data sets to OpenStreetMap. The opinions about these data imports are divergent among researchers and contributors, and the subject is constantly discussed. The question of whether importing data, especially large quantities, is adding value to OSM or compromising the progress of the project needs to be investigated more deeply. For this study, OSM’s historical data were used to compute metrics about the developments of the contributors and OSM data during large data imports which were for the Netherlands and India. Additionally, one time period per study area during which there was no large data import was investigated to compare results. For making statements about the impacts of large data imports in OSM, the metrics were analysed using different techniques (cross-correlation and changepoint detection). It was found that the contributor activity increased during large data imports. Additionally, contributors who were already active before a large import were more likely to contribute to OSM after said import than contributors who made their first contributions during the large data import. The results show the difficulty of interpreting a heterogeneous data source, such as OSM, and the complexity of the project. Limitations and challenges which were encountered are explained, and future directions for continuing in this field of research are given.

Research on weak signal detection of integral average digital lock-in amplifier

In the process of detecting the amplitude and phase of the weak signal based on digital lock-in amplifier (DLIA), a low-pass filter (LPF) with an extremely low cut-off frequency is required. Even so, the effect is often not good. The detection results of amplitude and phase of weak signal are distorted and fluctuate sharply. To eliminate the difficulty of LPF design, and to reduce the distortion and output fluctuation of detection results of DLIA, this paper proposes a weak signal detection method based on integral average digital lock-in amplifier (IADLIA), which can be used for weak signal detection under strong noise. This method optimizes the structure of the traditional DLIA based on the principle of cross-correlation detection. And then this paper analyzes the influence of the cut-off frequency and signal-to-noise ratio of the LPF on the detection accuracy and output stability of the weak signal amplitude and phase. Finally, the corresponding weak-signal amplitude at the bearing rotating frequency is accurately detected by the proposed method, and the accurate identification of bearing faults is realized. The experimental results show that the IADLIA is characterized by stable output, strong anti-interference ability and high output accuracy. The proposed method can accurately detect the amplitude and phase information of the weak signal in a strong noise environment, get rid of the structure of LPF, and the overall performance is better than the traditional DLIA.

Noninvasive Acoustic Measurements in Cylindrical Shell Containers.

Acoustic time-of-flight (ToF) measurements enable noninvasive material characterization, acoustic imaging, and defect detection and are commonly used in industrial process control, biomedical devices, and national security. When characterizing a fluid contained in a cylinder or pipe, ToF measurements are hampered by guided waves, which propagate around the cylindrical shell walls and obscure the waves propagating through the interrogated fluid. We present a technique for overcoming this limitation based on a broadband linear chirp excitation and cross correlation detection. By using broadband excitation, we exploit the dispersion of the guided waves, wherein different frequencies propagate at different velocities, thus distorting the guided wave signal while leaving the bulk wave signal in the fluid unperturbed. We demonstrate the measurement technique experimentally and using numerical simulation. We characterize the technique performance in terms of measurement error, signal-to-noise-ratio, and resolution as a function of the linear chirp center frequency and bandwidth. We discuss the physical phenomena behind the guided bulk wave interactions and how to utilize these phenomena to optimize the measurements in the fluid.

Application of Subspace-Based Detection Algorithm to Infrasound Signals in Volcanic Areas

Infrasonic signals investigation plays a fundamental role for both volcano monitoring purpose and the study of the explosion dynamics. Proper and reliable detection of weak signals is a critical issue in active volcano monitoring. In particular, in volcanic acoustics, it has direct consequences in pinpointing the real number of generated events (amplitude transients), especially when they exhibit low amplitude, are close in time to each other, and/or multiple sources exist. To accomplish this task, several algorithms have been proposed in literature; in particular, to overcome limitations of classical approaches such as short-time average/long-time average and cross-correlation detector, in this paper a subspace-based detection technique has been implemented. Results obtained by applying subspace detector on real infrasound data highlight that this method allows sensitive detection of lower energy events. This method is based on a projection of a sliding window of signal buffer onto a signal subspace that spans a collection of reference signals, representing similar waveforms from a particular infrasound source. A critical point is related to subspace design. Here, an empirical procedure has been applied to build the signal subspace from a set of reference waveforms (templates). In addition, in order to determine detectors parameters, such as subspace dimension and detection threshold, even in presence of overlapped noise such as infrasonic tremor, a statistical analysis of noise has been carried out. Finally, the subspace detector reliability and performance, have been assessed by performing a comparison among subspace approach, cross-correlation detector and short-time average/long-time average detector. The obtained confusion matrix and extrapolated performance indices have demonstrated the potentiality, the advantages and drawbacks of the subspace method in tracking volcanic activity producing infrasound events. This method revealed to be a good compromise in detecting low-energy and very close in time events recorded during Strombolian activity.

Dynamic Measurement of Well Inclination Based on UKF and Correlation Extraction

While drilling, the drilling tool can reach the target layer more quickly and efficiently with the accurate borehole trajectory information. It can reduce the drilling cost. However, in the process of traditional well inclination measurement with drilling, due to the interference form the rotary vibration of drill string, the inclinometer needs to stop drilling to complete the measurement of drill tool attitude. And the sensor is installed far away from the drill, so the measurement error and the risk of well control are increased. In order to solve the problem that the interference of near the bit inclinometer which caused by complex shock vibration and drill string rotation, this paper proposes a method of dynamic measuring inclination angle that based on unscented kalman filter and cross-correlation extraction algorithm (UKF+CC). It is a composite filtering method that combine UKF, cross-correlation extraction algorithm, low pass filtering with sliding slide filtering. In this method, firstly, a limiter filter is used to filter the step excitation signal caused by impact noise. Then UKF filter is used to filter out the most colored noise caused by vibration acceleration, at the same time, low-pass filtering is used to deal with the magnetic interference noise in the output signal of tri-axis fluxgate, and using sliding filter to smooth the radial acceleration signal in the tri-axis acceleration sensor. Finally, the radial or tangential direction magnetic signal of the tri-axis fluxgate is used as the reference signal, and use reference signal to extract accurately the gravity acceleration component of the near bit position by cross-correlation detection method, then can finish the accurate calculation of dynamic well inclination angle. The results are verified by the simulation test and the simulation experiment of the rotating vibration test platform. When the drilling tool rotation speed within 60-300r/min, the maximum measurement error is +0.09°, the overall measurement accuracy of inclination angle under different drilling tool rotation speed is better than ±0.1°and the measured results are not affected by the rotation speed and vibration of drilling tool, it realizes the dynamic and accurate measurement of the inclination angle in the process of drilling.

An Algorithm to Minimize the Zero-Flow Error in Transit-Time Ultrasonic Flowmeters

Transit-time ultrasonic flowmeters are widely used in industry to measure fluid flow. In practice, ultrasonic flowmeters either show a zero-flow error or suffer from a significant random error due to a limited signal-to-noise ratio, requiring a significant amount of averaging to achieve good precision. This work presents a method that minimizes the zero-flow error while keeping the random error low, independent of the hardware used. The proposed algorithm can adjust to changing zero-flow errors, while a flow is present. The technique combines the benefits of two common methods of determining the transit time difference between the upstream and downstream ultrasonic waves: cross correlation and zero-crossing detection. The algorithm is verified experimentally using a flow loop. It is shown that the zero-flow error can be greatly reduced without compromising the random error or increasing circuit complexity.

Neural correlates of extremely large individual differences in interaural cross-correlation detection

Interaural cross-correlation is a primary feature that can predict the detection of dichotic signals in background noise. Perfectly correlated noise presented to the two ears is perceived as compact and centrally lateralized. As noise is binaurally de-correlated, the perceptual image widens and becomes more diffuse. Previous investigators have reported large variability across individuals' cross correlation just-noticeable differences (IACC-JNDs). Anecdotally, many listeners with normal pure tone thresholds present as extreme outliers in binaural tasks. It is unknown whether or not this variability across individuals is reflected in the neural activity recorded during passive listening to these stimuli. IACC-JNDs were measured in a behavioral task and compared to correlation-change evoked potentials using electroencephalography (EEG). Results indicate significantly smaller cortical responses (N1 and P2 amplitudes) to interaural change differences for individuals with large- compared to small-JND thresholds. Source localization of this effect was observed in multiple subdivisions of the auditory cortex, include Heschl's gyrus, planum temporale, and the temporal sulcus. These results provide objective electrophysiological evidence of a binaural processing deficit corresponding to extremely large JND thresholds. Interestingly, these listeners are indeed binaurally disadvantaged despite otherwise normal audiometric profiles and lack of spatial hearing complaints. [Work supported by NIH P01AG009524.]

Analysis of High-Resolution Underwater Acoustic Imaging Technology in Multi-Subarray Beam Domain

Chu, P.; Zhang, L.; Huo, W.; Wang, K., and Chen, Y., 2020. Analysis of high-resolution underwater acoustic imaging technology in multi-subarray beam domain. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 518–521. Coconut Creek (Florida), ISSN 0749-0208.The development of ocean resources and the research of ocean engineering are inseparable from the acquisition and mastery of underwater scene information, and the most important way to obtain this information is underwater acoustic imaging technology. This paper is divided into two parts: theoretical research and model simulation. In the theoretical research, the principle of traditional the split-beam phase detection method and the basic principle of cross-correlation detection technology of the phase center in beam domain are analyzed. Then, the signal model is established, and the conclusion that the number of subarray elements is positively correlated with the resolution of the system is obtained. Finally, the simulation model of the seabed is established to verify the algorithm of multi-subarray beam domain seabed detection and the high-resolution underwater acoustic imaging system.

Prediction of unmeasurable parameters of NPPs using different model-free methods based on cross-correlation detection of measurable/unmeasurable parameters: A comparative study

In this paper cross-correlation of measurable/unmeasurable parameters of nuclear power plants (NPPs) are detected. Correlation techniques including Pearson’s, Spearman’s, and Kendall-tau give appropriate input parameters for training/prediction of the target unmeasurable parameters. Fuel and clad maximum temperatures of uncontrolled withdrawal of control rods (UWCR) transient of Bushehr nuclear power plant (BNPP) are used as the case study target parameters. Different model-free methods including decision tree (DT), feed-forward back propagation neural network (FFBPNN) accompany with different learning algorithms (i.e. gradient descent with momentum (GDM), scaled conjugate gradient (SCG), Levenberg-Marquardt (LM), and Bayesian regularization (BR)), and support vector machine (SVM) with different kernel functions (i.e. linear and Gaussian functions) are employed to predict the target parameters. Comparison of the results indicates that BR learning algorithm of FFBPNN gives more precise results. Moreover, DT results is comparable with LM learning algorithm of FFBPNN. In addition, SVM results with Gaussian kernel function is better than SVM results with linear one. Results show that cross-correlation detection among the parameters has decisive effect on performance of learning algorithms. This claim is verified by prediction of the target parameters using either fewer number of correlated input parameters or uncorrelated input parameters. The input parameters without strong correlation have greater errors in forecasting. In addition, more parameters with strong correlation give better results. Prediction of unmeasurable parameters of NPPs can be used as a support system for the NPPs operators to perform more appropriate actions in confrontation with transients.