Narrowband Signals Research Articles

Classification for Memory Activities: Experiments and EEG Analysis Based on Networks Constructed via Phase-Locking Value.

Electroencephalogram (EEG) plays a crucial role in the study of working memory, which involves the complex coordination of brain regions. In this research, we designed and conducted series of experiments of memory with various memory loads or target forms and collected behavioral data as well as 32-lead EEG simultaneously. Combined with behavioral data analysis, we segmented EEG into slices; then, we calculated phase-locking value (PLV) of Gamma rhythms between every two leads, conducted binarization, constructed brain function network, and extracted three network characteristics of node degree, local clustering coefficient, and betweenness centrality. Finally, we inputted these network characteristics of all leads into support vector machines (SVM) for classification and obtained decent performances; i.e., all classification accuracies are greater than 0.78 on an independent test set. Particularly, PLV application was restricted to the narrow-band signals, and rare successful application to EEG Gamma rhythm, defined as wide as 30-100 Hz, had been reported. In order to address this limitation, we adopted simulation on band-pass filtered noise with the same frequency band as Gamma to help determine the PLV binarizing threshold. It turns out that network characteristics based on binarized PLV have the ability to distinguish the presence or absence of memory, as well as the intensity of the mental workload at the moment of memory. This work sheds a light upon phase-locking investigation between relatively wide-band signals, as well as memory research via EEG.

A Fingerprint-Based Indoor Localization System Using IEEE 802.15.4 for Staying Room Detection

Nowadays, indoor localization systems using IEEE 802.11 have been actively explored for location-based services, since GPS cannot identify floors or rooms in buildings. However, the user-side device is usually large and consumes high energy. In this paper, the authors propose a fingerprint-based indoor localization system using IEEE 802.15.4 that allows the use of a small device with a long-life battery, named FILS15.4. A user carries a small transmitter whose signal is received by multiple receivers simultaneously. The received signal strengths are compared with the fingerprints to find the current location. To address signal fluctuations caused by the low-power narrow-band signal, FILS15.4 limits one room as the localization unit, prepares plural fingerprints for each room, and allocates a sufficient number of receivers in the field. For evaluations, extensive experiments were conducted at #2 Engineering Building in Okayama University and confirmed high detection accuracy with sufficient numbers of receivers and fingerprints.

All-sky, all-frequency directional search for persistent gravitational waves from Advanced LIGO’s and Advanced Virgo’s first three observing runs

We present the first results from an all-sky all-frequency (ASAF) search for an anisotropic stochastic gravitational-wave background using the data from the first three observing runs of the Advanced LIGO and Advanced Virgo detectors. Upper limit maps on broadband anisotropies of a persistent stochastic background were published for all observing runs of the LIGO-Virgo detectors. However, a broadband analysis is likely to miss narrowband signals as the signal-to-noise ratio of a narrowband signal can be significantly reduced when combined with detector output from other frequencies. Data folding and the computationally efficient analysis pipeline, PyStoch, enable us to perform the radiometer map-making at every frequency bin. We perform the search at 3072 HEALPix equal area pixels uniformly tiling the sky and in every frequency bin of width 1/32 Hz in the range 20–1726 Hz, except for bins that are likely to contain instrumental artefacts and hence are notched. We do not find any statistically significant evidence for the existence of narrowband gravitational-wave signals in the analyzed frequency bins. Therefore, we place 95% confidence upper limits on the gravitational-wave strain for each pixel-frequency pair, the limits are in the range (0.030−9.6)×10−24. In addition, we outline a method to identify candidate pixel-frequency pairs that could be followed up by a more sensitive (and potentially computationally expensive) search, e.g., a matched-filtering-based analysis, to look for fainter nearly monochromatic coherent signals. The ASAF analysis is inherently independent of models describing any spectral or spatial distribution of power. We demonstrate that the ASAF results can be appropriately combined over frequencies and sky directions to successfully recover the broadband directional and isotropic results.Received 25 October 2021Revised 22 February 2022Accepted 17 May 2022DOI:https://doi.org/10.1103/PhysRevD.105.122001© 2022 American Physical SocietyPhysics Subject Headings (PhySH)Research AreasGravitational wave detectionGravitational wavesGravitation, Cosmology & Astrophysics

Direction Finding for Multiple Wideband Chirp Signal Sources using Blind Signal Separation and Matched Filtering

This paper proposes a new scheme to estimate the direction-of-arrival (DOA) of multiple wideband chirp signals. The proposed scheme comprises three steps: 1) preprocessing of the mixed signal using independent component analysis in order to obtain each wideband chirp signal; 2) matched filtering in order to transform the multiple wideband chirp signals into narrowband signals; and 3) the estimation of final DOAs using the conventional subspace-based method. In order to validate the effectiveness of the proposed scheme, we carried out extensive experiments, including three different scenarios: non-overlapped in the frequency domain, overlapped in the frequency domain, and nonlinear chirp signal cases. From the experimental results, we can conclude that the proposed scheme provides not only accurate results in terms of root-mean-squared error (RMSE), but also the lowest computational complexity compared to the previous methods.

Multiple Angles of Arrival Estimation Using Broadband Signals and a Nonuniform Planar Array

As the requirements related to resolution or the data rate increase, most angle-of-arrival (AoA) estimation problems can be assumed to be under a broadband signal model. In this paper, AoA estimation using a nonuniform planar array (NUPA), which aims to resolve more signals and reduce mutual coupling, is considered under a broadband signal model. The analysis is conducted in both the space and frequency domains, and a broadband co-array is proposed to improve the performance of the AoA estimation. The broadband co-array is generated as follows: First, the received broadband signal is decomposed into several narrowband signals, and the samples from different frequency bins are transformed to space-domain samples to generate a virtual array. Then, the second-order statistics of the virtual array are used to generate the broadband co-array. The virtual array can decrease the number of element pairs with small interelement spacing to reduce mutual coupling in AoA estimations. With the help of the virtual array, the following broadband co-array can greatly increase the degrees of freedom, resulting in more resolvable signals and lower Cramer-Rao bounds of AoA estimation. An optimization method based on sparse recovery is proposed to locate the array. The simulation results confirm the AoA estimation performance achieved by the designed NUPA.

Searching for Broadband Pulsed Beacons from 1883 Stars Using Neural Networks

The search for extraterrestrial intelligence at radio frequencies has largely been focused on continuous-wave narrowband signals. We demonstrate that broadband pulsed beacons are energetically efficient compared to narrowband beacons over longer operational timescales. Here, we report the first extensive survey searching for such broadband pulsed beacons toward 1883 stars as a part of the Breakthrough Listen’s search for advanced intelligent life. We conducted 233 hr of deep observations across 4–8 GHz using the Robert C. Byrd Green Bank Telescope and searched for three different classes of signals with artificial (or negative) dispersion. We report a detailed search—leveraging a convolutional neural network classifier on high-performance GPUs—deployed for the very first time in a large-scale search for signals from extraterrestrial intelligence. Due to the absence of any signal-of-interest from our survey, we place a constraint on the existence of broadband pulsed beacons in our solar neighborhood: ≲1 in 1000 stars have transmitter power densities ≳105 W Hz−1 repeating ≤500 s at these frequencies.

Some features of Hilbert transform and their use in energy informatics

Information-measuring technologies (IMT) are an important instrument for solving problems of energy informatics. They allow to form primary information based on the interaction of energy facilities with IMT sensors that form information signals. In many practical applications, the constructive model of information signals is the model of narrowband signals. The article summarizes the features of the discrete Hilbert transform and its application to obtain the primary characteristics of information signals – bypass and phase as functions of time. The main advantages of using the discrete Hilbert transform in signal processing for energy informatics are considered, including the consistency of obtaining frequency and time characteristics, high information content, the ability to analyze the dynamics of changes in signal characteristics, the possibility of obtaining samples of characteristics of information signals of significant volumes, etc. It is proposed to use a phase characteristic to select the time interval that limits the signal sample and sets it to a multiple of the signal period, and the sampling rate of information signals to reduce the errors in estimating their spectrum. The possibility of obtaining on their basis secondary deterministic (voltage level, voltage deviations from the nominal level, attenuation coefficient, signal period, signal phase shift, oscillation frequency, etc.) and statistical (sample characteristic, sample variance, sample median, sample circular variance, sample circular median, sample circular kurtosis, etc.) of signal information characteristics, which allows more complete to use their information resource. These characteristics can be used both for assessing power quality characteristics and for monitoring and diagnosing of energy facilities. Keywords: energy informatics, information signals, signal processing, discrete Hilbert transform, amplitude signal characteristics, phase signal characteristics

Bridge damage detection using reconstructed mode shape by improved vehicle scanning method

In this study, the improved vehicle scanning method (VSM) is adopted for structural health monitoring to identify healthy and damaged states of bridges. The improved VSM uses a designed elliptic filter (instead of the conventional Butterworth filter) to obtain the narrowband signals from the contact point response. These high-quality narrowband signals are able to furnish accurate vibration modes that reveal kinks that indicate the damage locations in the bridges. This improved VSM works best with a series of vehicles that are modeled as moving sprung masses passing over the bridge. The exciting vehicles modeled by heavier masses excite the bridge, and they are followed by a testing vehicle modeled by lighter masses to capture the acceleration response at the contact point. Some example problems involving bridges with different damage locations and severities were studied. It is shown herein that the improved VSM extracted mode shapes have very visible kinks to mark the damage positions of the bridges when compared to mode shapes extracted from existing VSMs. So, the improved VSM is able to directly pinpoint the damage locations from the extracted mode shapes with minimal postprocessing effort, whereas existing VSMs generally require additional effort, e.g., constructed damage indices, for damage identification. To better identify the damage locations, a few higher modes should be used so as to avoid missing the damage locations at nodes of a particular vibration mode.

Cascaded nanobeam spectrometer with high resolution and scalability

An on-chip reconstruction spectrometer provides a powerful approach for miniaturized and portable applications. Owing to the cross-correlation and line shape of broadband responses, the reconstruction spectrometer exhibits limited resolution and a fixed bandwidth. Here we demonstrate a cascaded nanobeam spectrometer with assistance of a reconstruction algorithm. The transmissions of tunable Fano-enhanced nanobeams (FENs) are of good orthogonality and have improved quality factors. We retrieved a narrowband signal of 0.16 nm linewidth and a dual peak at 0.32 nm distance for resolution characterization. This result breaks the limit of the full width at half maximum for narrowband filter spectrometers. An expanded bandwidth is realized by a three-channel cascaded device, and signal spectra in the 16 nm range are reconstructed successfully. Each FEN unit has an ultra-compact footprint of 18 × 18 µ m 2 . In view of the improved performance and flexibility, our concept is an ideal candidate for precise and miniaturized applications.

Information transmission in recurrent networks: Consequences of network noise for synchronous and asynchronous signal encoding.

Information about natural time-dependent stimuli encoded by the sensory periphery or communication between cortical networks may span a large frequency range or be localized to a smaller frequency band. Biological systems have been shown to multiplex such disparate broadband and narrow-band signals and then discriminate them in later populations by employing either an integration (low-pass) or coincidence detection (bandpass) encoding strategy. Analytical expressions have been developed for both encoding methods in feedforward populations of uncoupled neurons and confirm that the integration of a population's output low-pass filters the information, whereas synchronous output encodes less information overall and retains signal information in a selected frequency band. The present study extends the theory to recurrent networks and shows that recurrence may sharpen the synchronous bandpass filter. The frequency of the pass band is significantly influenced by the synaptic strengths, especially for inhibition-dominated networks. Synchronous information transfer is also increased when network models take into account heterogeneity that arises from the stochastic distribution of the synaptic weights.

Broadband Acoustic Communication Aided Underwater Inertial Navigation System

We present an underwater localization system for medium-sized Autonomous Underwater Vehicles (AUVs) that leverages a broadband wireless acoustic communication system for GPS-denied underwater localization. Many current acoustic localization systems assume a single line-of-sight path and use either narrow-band signals or short-duration pings for the convenience of mitigating motion-induced Doppler at the expense of the time-of-arrival (TOA) accuracy and operational flexibility. We propose a novel acoustic localization system that utilizes the aggressive signal processing embedded in underwater acoustic communication systems to resolve multi-path and Doppler distortion and finely estimate timing information using broadband communication signals. Timing and Doppler information extracted from this process is then used to estimate biases and drift from an inertial navigation system (INS) using a Bayesian framework. To demonstrate the feasibility of the system model, co-simulations are created from the MACE10 experimental data. Our results show dramatic improvement in localization accuracy, with an error of less than 120 m achieved over the 3 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sim$</tex-math></inline-formula> 7 km distance range from the MACE 10 experiment between an AUV and a remote beacon with an acoustic communication transmission interval of 30 seconds.

Development of a real-time cavity-based injection efficiency monitor system at SSRF

Injection efficiency is a critical parameter for synchrotron radiation facilities, especially those operating in top-up mode. The Shanghai Synchrotron Radiation Facility (SSRF) started top-up operation in 2012 committed to providing users with higher-quality light sources. During the top-up operation, a regular injection from the booster to the storage ring is required. A low-efficiency injection system will massively increase the radiation dose and seriously threaten the health of users. To evaluate the performance of the injection system, a real-time injection efficiency measurement system with high-resolution and high reliability is indispensable. Instead of using an integrating current transformer (ICT) that requires extremely careful shielding and grounding, a new system uses a novel dual-cavity monitor that can generate a high signal-to-noise ratio (SNR) and narrowband signal to detect bunch charges. It aims to reduce the influence of electromagnetic interference on the system and improve the reliability and resolution of the system. This paper describes the establishment of a cavity-based injection efficiency measurement system and focuses on bunch charge calibration and tests of the system resolution and injection efficiency. The test results show that the system resolution is 0.34% and the average injection efficiency is close to 90% at regular top-up operation.

Testing the generation of harmonic templates from coincidence patterns in response to noise: Physiological and modeling considerations

Harmonic templates are a critical component of spectral pitch theories. Shamma and Klein (2000) hypothesize that such templates can arise from neural coincidence patterns in response to stochastic stimuli without pitch.The key feature of their computational model is a higher number of coincidences between neurons with harmonically related characteristic frequencies (CFs). We tested the hypothesis with physiological data and a computational model. We recorded neural responses in chinchilla to various periodic and non-periodic stimuli, both from the auditory nerve and the trapezoid body. We then examined counts of spike coincidences across fibers. The key prediction of a higher number of coincidences between pairs of fibers with harmonically related CFs than for other pairs was observed for responses to narrowband signals (tones at CF), but not to broadband noise. We then tested a model similar to that of Shamma and Klein. Only with cochlear filters sharper than plausible even in humans, followed by additional spectral sharpening through lateral inhibition and extreme temporal sharpening, do we obtain harmonic templates similar to their model. Although our results do not speak to the existence of harmonic templates per se, we conclude that the specific mechanism of this hypothesis has little physiological plausibility.

ILLOC

LoRaWAN is a narrowband wireless technology for ubiquitous connectivity. For various applications, it is desirable to localize LoRaWAN devices based on their uplink frames that convey application data. This localization service operates in an unobtrusive manner, in that it requires no special software instrumentation to the LoRaWAN devices. This paper investigates the feasibility of unobtrusive localization for LoRaWAN devices in hall-size indoor spaces like warehouses, airport terminals, sports centers, museum halls, etc. We study the TDoA-based approach, which needs to address two challenges of poor timing performance of LoRaWAN narrowband signal and nanosecond-level clock synchronization among anchors. We propose the ILLOC system featuring two LoRaWAN-specific techniques: (1) the cross-correlation among the differential phase sequences received by two anchors to estimate TDoA and (2) the just-in-time synchronization enabled by a specially deployed LoRaWAN end device providing time reference upon detecting a target device's transmission. In a long tunnel corridor, a 70 x 32 m2 sports hall, and a 110 x 70 m2 indoor plaza with extensive non-line-of-sight propagation paths, ILLOC achieves median localization errors of 6 m (with 2 anchors), 8.36 m (with 6 anchors), and 15.16 m (with 6 anchors and frame fusion), respectively. The achieved accuracy makes ILLOC useful for applications including zone-level asset tracking, misplacement detection, airport trolley management, and cybersecurity enforcement like detecting impersonation attacks launched by remote radios.

Accumulatively Increasing Sensitivity of Ultrawide Instantaneous Bandwidth Digital Receiver with Fine Time and Frequency Resolution for Weak Signal Detection

It is always an interesting research topic for digital receiver (DRX) designers to develop a DRX with (1) ultrawide instantaneous bandwidth (IBW), (2) high sensitivity, (3) fine time-of-arrival-measurement resolution (TMR), and (4) fine frequency-measurement resolution (FMR) for weak signal detection. This is because designers always want their receivers to have the widest possible IBW to detect far away and/or weak signals. As the analog-to-digital converter (ADC) rate increasing, the modern DRX IBW increases continuously. To improve the signal detection based on blocking FFT (BFFT) method, this paper introduces the new concept of accumulatively increasing receiver sensitivity (AIRS) for DRX design. In AIRS, a very large number of frequency-bins can be used for a given IBW in the time-to-frequency transform (TTFT), and the DRX sensitivity is cumulatively increased, when more samples are available from high-speed ADC. Unlike traditional FFT-based TTFT, the AIRS can have both fine TMR and fine FMR simultaneously. It also inherits all the merits of the BFFT, which can be implemented in an embedded system. This study shows that AIRS-based DRX is more efficient than normal FFT-based DRX in terms of using time-domain samples. For example, with a probability of false alarm rate of 10−7, for N=220 frequency-bins with TMR = 50 nSec, FMR = 2.4414 KHz, IBW &gt; 1 GHz and ADC rate at 2.56 GHz, AIRS-based DRX detects narrow-band signals at about −42 dB of input signal-to-noise ratio (Input-SNR), and just uses a little less than N/2 real-samples. However, FFT-based DRX have to use all N samples. Simulation results also show that AIRS-based DRX can detect frequency-modulated continuous wave signals with ±0.1, ±1, ±10 and ±100 MHz bandwidths at about −39.4, −35.1, −30.2, and −25.5 dB of Input-SNR using about 264.6 K, 104.7 K, 40.2 K and 18.3 K real-samples, respectively, in 220 frequency-bins for TTFT.

Accuracy of narrow-band spectral indices estimation by wide-band remote sensing data

Narrow-band spectral indices are quite informative and important in various applications of remote sensing – to assess the condition of vegetation, soils, water bodies and other land surface formations. However, direct measurement of narrow-band spectral indices requires hyperspectral imaging. But most of modern multispectral aerospace imaging systems are wide-band. Accordingly, it is not possible to calculate the narrow-band index directly from wide-band remote sensing data. This paper discusses approaches to the narrow-band spectral indices restoration by wide-band remote sensing data using statistical models of interrelations of narrow- and wide-band indices itself, of source wide-band and narrow-band signals in close spectral bands, as well as of land surface reflectance quasi-continuous spectra translation from wide bands to narrow ones.The experimental accuracy estimation of narrow-band spectral indices restoration by wide-band multispectral satellite image is performed. Three most complicated narrow-band spectral indices, which covering a range of spectrum from visible to short-wave infrared, were considered, namely – the transformed chlorophyll absorption in reflectance index (TCARI), the optimized soil-adjusted vegetation index (OSAVI) and the normalized difference nitrogen index (NDNI). All three mentioned methods for narrow-band spectral indices restoration are analyzed. The worst result is demonstrated for regression-restored signals in spectral bands, and the best result is for the spectra translation method. Therefore, the method on the basis of spectra translation is recommended for practical implementation.

Simultaneous Localization and Communication Method Using Short-Time and Narrow-Band Dual-Carrier Acoustic Signals

This paper describes a novel acoustic localization and communication methods using multiple speakers. Acoustic signals for localization are modulated by differential phase shift keying to contain some information. Therefore, localization and communication can be conducted simultaneously. Regarding the design of acoustic signals, short-time and narrow-band acoustic signals are ideal to save time and frequency resources. However, if such signals are used with conventional methods, the interference of signals can occur and cause errors of localization and communication. Additionally, this error changes depending on the phase value that corresponds to the modulation for communication. To reduce this error, in our proposed method, a noninterference region in the received signal was constituted by using dual-carrier acoustic signals, and localization and demodulation were processed using this region. In the evaluation experiments, we estimate the azimuth of the microphone from two speakers and demodulate each of the symbols at 9 locations. Through simulation and real-environment experiments, it was confirmed that our proposed method can reduce the error caused by the interference. In real-environment experiments, the demodulation performance of our proposed method was similar to that of conventional methods. We discussed this similarity and revealed the cause.

Spatial deception suppression for wideband linear frequency modulation signals based on fractional Fourier transform with robust adaptive beamforming

Wideband linear frequency modulation (LFM) signal is popular for target detection and imaging in wideband array radar systems. In this paper, a novel and robust adaptive wideband digital beamforming (DBF) algorithm is proposed for suppressing the deception jamming of wideband LFM signals. Firstly, wideband LFM echoes are treated as narrowband signals using fractional Fourier transform (FrFT) with a specific order. Secondly, a robust and adaptive narrowband DBF method based on steering vector estimation, covariance matrix reconstruction, and low-pass filtering are applied to suppress deception jamming. Finally, the inverse FrFT is performed to transform the processing results back to the time-domain wideband signals. Compared with the conventional time- and frequency-domain wideband beamformers, the proposed algorithm significantly reduces the amount of calculation and computational complexity. The simulation results indicate that the proposed algorithm can effectively suppress deception jamming, and its interference suppression capability is approximately like that of an optimal beamformer. Furthermore, the validity and effectiveness of the proposed algorithm are verified with the experimental data in a microwave anechoic chamber.

Experimental study of passive detection of underwater targets across ice

This study deployed receivers and sources of sound on the Songhua River and the Arctic Ice Station—areas covered with ice—in field experiments to examine and verify the feasibility of the passive detection of narrowband signals of underwater targets across ice. The classic method for the detection of narrowband signals based on power spectrum estimation was used. However, the spectrum was noisy, making it difficult to establish a detection threshold, which in turn, affected the results of detection. To solve this problem, an α-comparative detector based on the one-dimensional Kalman filter was developed to smoothen the frequency domain and improve detection capability. The results of experimental data processing show that under special impulse noise interference in areas covered with ice, the proposed method of signal processing reduced signal interference in the frequency domain to enable a clearer observation of narrowband signals. The feasibility of using the proposed method for the passive detection of narrowband signals of underwater targets across ice was also verified.

A study on the performance evaluation of wavelet decomposition in transient‐based radio frequency fingerprinting of Bluetooth devices

AbstractRadio frequency fingerprinting (RFF) is used as a physical‐layer security method to provide security in wireless networks. Basically, it exploits the distinctive features (fingerprints) extracted from the physical waveforms emitted from radio devices in the network. One of the major challenges in RFF is to create robust features forming the fingerprints of radio devices. Here, dual‐tree complex wavelet transform (DT‐CWT) provides an accurate way of extracting those robust features. However, its performance on the RFF of Bluetooth transients which fall into narrowband signaling has not been reported yet. Therefore, this study examines the performance of DT‐CWT features on the use of transient‐based RFF of Bluetooth devices. Initially, experimentally collected Bluetooth transients from different smartphones are decomposed by DT‐CWT. Then, the characteristics and statistics of the wavelet domain signal are exploited to create robust features. Next, the support vector machine (SVM) is used to classify the smartphones. The classification accuracy is demonstrated by varying channel signal‐to‐noise ratio (SNR) and the size of transient duration. Results show that reasonable accuracy can be achieved (lower bound of 88%) even with short transient duration (1024 samples) at low SNRs (0–5 dB).