Wideband Sources Research Articles

Sparse reconstruction methods for wideband source localization in spherical harmonics domain

Wideband acoustic source localization is a challenging task especially in the presence of noise. Generally wideband source localization is done by averaging the Direction of Arrival (DOA) estimates obtained over multiple frequencies or narrow subbands by the method of frequency smoothing. Localization of multiple wideband sources which are correlated is even more challenging. In this work acoustic source localization under these challenging conditions is addressed. A sparse reconstruction framework is developed for wideband source localization in the Spherical Harmonics (SH) domain. The proposed framework jointly computes both the azimuth and elevation. In contrast to earlier methods of source localization in the SH domain, this work utilizes the expression for the SH coefficients of the amplitude density of the plane wave, to develop the sparse reconstruction framework. An expression for Cramér Rao Lower Bound (CRLB) on the DOA using this framework is also derived for the wideband sources. This CRLB is shown to easily generalize for narrowband sources as well. The performance of the proposed method is compared with MUltiple Signal Classification in SH domain (MUSIC-SH), Steered Response Power in SH domain (SRP-SH), MUSIC with Direct Path Dominance test in SH domain (MUSIC-DPD-SH) and Pressure based Compressive Sensing in SH domain (PCS-SH). The performance is evaluated for correlated narrowband and wideband sources through simulations, conducting experiments in an anechoic chamber and under reverberant conditions. Using the proposed framework, it is shown that correlated narrowband and wideband sources can be resolved reasonably well when compared to conventional methods of acoustic source localization in SH domain.

Advancements in wideband source localization with an acoustic vector sensor line array

A method is presented for localizing wideband acoustic sources using an array of acoustic vector sensors (AVS). The method focuses on leveraging the lack of correlation between acoustic pressure and particle velocity in the underwater environmental noise field. Coherent processing is introduced in the signal processing stage to suppress noise components in the observed data. By employing a focused transform that maps various frequency components of the wideband signal into the same signal subspace, an asymptotically unbiased Direction of Arrival (DOA) estimation is achieved using a multidimensional subspace method. A concise expression for the Cramér-Rao Bound (CRB) on the estimation errors is provided within the framework of the wideband multi-vector-sensor model. The performance of the proposed method for localizing sources is assessed through simulation and experimental data analysis. The research indicates that coherent processing effectively suppresses isotropic components in background noise, the proposed method achieves a lower estimation error, closer to the CRB, compared to the scalar array counterpart under identical signal-to-noise ratio (SNR) conditions.

Direction-of-Arrival Estimation via Sparse Bayesian Learning Exploiting Hierarchical Priors with Low Complexity.

For direction-of-arrival (DOA) estimation problems in a sparse domain, sparse Bayesian learning (SBL) is highly favored by researchers owing to its excellent estimation performance. However, traditional SBL-based methods always assign Gaussian priors to parameters to be solved, leading to moderate sparse signal recovery (SSR) effects. The reason is Gaussian priors play a similar role to l2 regularization in sparsity constraint. Therefore, numerous methods are developed by adopting hierarchical priors that are used to perform better than Gaussian priors. However, these methods are in straitened circumstances when multiple measurement vector (MMV) data are adopted. On this basis, a block-sparse SBL method (named BSBL) is developed to handle DOA estimation problems in MMV models. The novelty of BSBL is the combination of hierarchical priors and block-sparse model originating from MMV data. Therefore, on the one hand, BSBL transfers the MMV model to a block-sparse model by vectorization so that Bayesian learning is directly performed, regardless of the prior independent assumption of different measurement vectors and the inconvenience caused by the solution of matrix form. On the other hand, BSBL inherited the advantage of hierarchical priors for better SSR ability. Despite the benefit, BSBL still has the disadvantage of relatively large computation complexity caused by high dimensional matrix operations. In view of this, two operations are implemented for low complexity. One is reducing the matrix dimension of BSBL by approximation, generating a method named BSBL-APPR, and the other is embedding the generalized approximate message passing (GAMB) technique into BSBL so as to decompose matrix operations into vector or scale operations, named BSBL-GAMP. Moreover, BSBL is able to suppress temporal correlation and handle wideband sources easily. Extensive simulation results are presented to prove the superiority of BSBL over other state-of-the-art algorithms.

Deep sediment characterization from very low-frequency features from merchant ships

The very low-frequency noise from merchant ships provides a good wideband source to study the deep layers of the seabed. The nested striations which characterize ship spectrograms contain unique acoustic features where the waveguide invariant (β) becomes infinite. This occurs at frequencies between 20 and 80 Hz where pairs of modal group velocities are equal. The goal of this project was to identify the β = ∞ frequencies in ship noise spectrograms and use these frequencies to perform statistical inference for the deep layer sound speeds and thicknesses. The Seabed Characterization Experiment of 2022 on the New England continental shelf had three vertical line arrays strategically placed between two shipping lanes. The average water depth was 75 meters with less than one meter bathymetry change between the arrays. The results of this study are based primarily on five ships. There was a gradual shift in the β = ∞ frequencies between the three arrays, suggesting a gradual change in the deep sediment layers. [Work supported by Office of Naval Research.]

Direction of arrival estimation using the rotating equatorial microphone

Introduction: Direction of arrival (DOA) estimation of sound sources is an essential task of sound field analysis which typically requires two or more microphones. In this study, we present an algorithm that allows for DOA estimation using the previously designed Rotating Equatorial Microphone prototype, which is a single microphone that moves rapidly along a circular trajectory, introducing DOA-dependent periodic distortions in the captured signal.Methods: Our algorithm compensates for the induced spectral distortions caused by the REM’s circular motion for multiple DOA candidates. Subsequently, the best DOA candidate is identified using two distortion metrics. We verify our approach through numerical simulations and practical experiments conducted in a low-reverberant environment.Results: The proposed approach localizes unknown single-frequency sources with a mean absolute error of 23 degrees and unknown wideband sources with a mean absolute error of 5.4 degrees in practice. Two sources are also localizable provided they are sufficiently separated in space.Conclusion: Whilst previous work only allowed for DOA estimation of a single monochromatic sound source with a known frequency, our DOA estimation algorithm enables localization of unknown and arbitrary sources with a single moving microphone.

ML-PMHT Tracking of Multiple Wideband Sources by Fusing Data from a Distributed Acoustic Vector Sensor Array

ML-PMHT Tracking of Multiple Wideband Sources by Fusing Data from a Distributed Acoustic Vector Sensor Array

Performance Comparison of Several Algorithms for Localization of Wideband Sources

In recent years, researchers have tried to estimate the direction-of-arrival (DOA) of wideband sources and several novel techniques have been proposed. In this paper, we compare six algorithms for calculating the DOA of broadband signals, namely coherent subspace signal method (CSSM), two-sided correlation transformation (TCT), incoherent multiple signal classification (IMUSIC), test of orthogonality of frequency subspaces (TOFS), test of orthogonality of projected subspaces (TOPS), and squared TOPS (S-TOPS). The comparison is made through computer simulations for different parameters, such as signal-to-noise ratio (SNR), in order to establish the efficiency and performance of the discussed methods in noisy environments. CSSM and TCT require initial values, but the remaining approaches do not need any preprocessing.

Direction of Arrival Estimation of Coherent Wideband Sources Using Nested Array.

Due to their ability to achieve higher DOA estimation accuracy and larger degrees of freedom (DOF) using a fixed number of antennas, sparse arrays, etc., nested and coprime arrays have attracted a lot of attention in relation to research into direction of arrival (DOA) estimation. However, the usage of the sparse array is based on the assumption that the signals are independent of each other, which is hard to guarantee in practice due to the complex propagation environment. To address the challenge of sparse arrays struggling to handle coherent wideband signals, we propose the following method. Firstly, we exploit the coherent signal subspace method (CSSM) to focus the wideband signals on the reference frequency and assist in the decorrelation process, which can be implemented without any pre-estimations. Then, we virtualize the covariance matrix of sparse array due to the decorrelation operation. Next, an enhanced spatial smoothing algorithm is applied to make full use of the information available in the data covariance matrix, as well as to improve the decorrelation effect, after which stage the multiple signal classification (MUSIC) algorithm is used to obtain DOA estimations. In the simulation, with reference to the root mean square error (RMSE) that varies in tandem with the signal-to-noise ratio (SNR), the algorithm achieves satisfactory results compared to other state-of-the-art algorithms, including sparse arrays using the traditional incoherent signal subspace method (ISSM), the coherent signal subspace method (CSSM), spatial smoothing algorithms, etc. Furthermore, the proposed method is also validated via real data tests, and the error value is only 0.2 degrees in real data tests, which is lower than those of the other methods in real data tests.

A High-Rigidity Organic-Inorganic Metal Halide Hybrid Enabling Reversible and Enhanced Self-Trapped Exciton Emission under High Pressure.

Zero-dimensional organic-inorganic metal halide hybrids provide ideal bulk-crystal platforms for exploring the pressure engineering of electron-phonon coupling (EPC) and self-trapped exciton (STE) emission at the molecular level. However, the low stiffness of inorganic clusters hinders the reversible tuning of these physical properties. Herein, we designed a Sb3+-doped metal halide with a high emission yield (89.4%) and high bulk modulus (35 GPa) that enables reversible and enhanced STE emission (20-fold) under pressure. The high lattice rigidity originates from the corner-shared cage-structured inorganic tetramers and ring-shaped organic ligands. Further, we reveal that the pressure-enhanced emission regime below 4.5 GPa is owing to the lattice hardening and preferably EPC strength reducing, while the pressure-insensitive emission regime within 4.5-8.5 GPa results from the enhanced intercluster Coulombic attraction force that resists intracluster compression. These results provide insights into the structure-property relation and molecular engineering of zero-dimensional metal halides toward wide-band and pressure-sensitive light sources.

Warm-core eddy effects on sound propagation in the South China sea

The spatial and temporal redistribution of sound energy caused by a warm eddy was measured via a multiday experiment conducted in the South China Sea, utilizing two vertical line arrays, a mooring source, and some wide-band explosive sources. In the experiment area, a warm eddy was identified and tracked using an automatic detection method combined with the empirically reconstructed data. During the experimental period, the warm eddy diminished in size and kinetic energy until it vanished. The influence of the warm eddy on sound propagation during its lifespan is comprehensively analyzed and explained. The experimental acoustic results and simulations based on dynamic hydrographic data demonstrate that energy is redistributed both spatially and temporally due to the presence of the warm eddy. In comparison to the environment without an eddy, the first convergence zone disappears and the high-energy region appears in the typical position of the first shadow zone. The oscillating disturbance in energy is mainly affected by the fluctuation of sound speed caused by the warm eddy.

Four-color fluorescence cross-correlation spectroscopy with one laser and one camera.

The diffusion and reorganization of phospholipids and membrane-associated proteins are fundamental for cellular function. Fluorescence cross-correlation spectroscopy (FCCS) measures diffusion and molecular interactions at nanomolar concentration in biological systems. We have developed an economical method to simultaneously monitor diffusion and complexation with the use of super-continuum laser and spectral deconvolution from a single detector. Customizable excitation wavelengths were chosen from the wide-band source and spectral fitting of the emitted light revealed the interactions for up to four chromatically overlapping fluorophores simultaneously. This method was applied to perform four-color FCCS that we demonstrated with polystyrene nanoparticles, lipid vesicles, and membrane-bound molecules. Up to four individually customizable excitation channels were selected from the broad-spectrum fiber laser to excite the diffusers within a diffraction-limited spot. The fluorescence emission passed through a cleanup filter and a dispersive prism prior to being collected by a sCMOS or EMCCD camera with up to 1.8 kHz frame rates. The emission intensity versus time of each fluorophore was extracted through a linear least-square fitting of each camera frame and temporally correlated via custom software. Auto- and cross-correlation functions enabled the measurement of the diffusion rates and binding partners. We have measured the induced aggregation of nanobeads and lipid vesicles in solution upon increasing the buffer salinity. Because of the adaptability of investigating four fluorophores simultaneously with a cost-effective method, this technique will have wide application for examining macromolecular complex formation in model and living systems.

A speed-amplified tri-stable piezoelectric-electromagnetic-triboelectric hybrid energy harvester for low-frequency applications

This work proposes a new speed-amplified multi-stable tri-hybrid energy harvesting technique via the multi-stable nonlinearity enhanced frequency up-conversion and rack-pinion mechanisms to efficiently harness structural and biomechanical vibration energy. In the present design, two frequency up-conversion piezoelectric generators, an array-type electromagnetic generator and a sliding-mode triboelectric nanogenerator are integrated together to form a compact and interactive system. By utilizing the rack-pinion mechanism, the relative speed between the stators and the translators of the electromagnetic and triboelectric generators are both doubled. Meanwhile, the process of frequency up-conversion in the piezoelectric generators is also doubled per each cycle. This results in better performance under wideband and low-frequency vibration sources. For verification, a prototype of this design is tested by mechanical excitations and body-induced motions. In the shaker test, the prototype can generate a peak output power of 446.16 mW under an optimal resistance load, resulting in a normalized power density of 4.20 mW cm–3 g–2 at 5 Hz under 1 g. The prototype also exhibits exceptional performance under various human motion tests, it can drive 600 commercial light-emitting diodes simultaneously. Using a commercial DC/DC voltage regulator circuit, the proposed harvester can serve as a universal power source to charge commercial electronic devices, including smartphones and GPS sensors. The present design shows great potential as a sustainable power source for wearable/portable electronics as well as wireless monitoring systems.

Gradient‐projection based super‐resolution wideband DOA estimation using non‐uniform linear arrays

AbstractA new method is developed for the Direction of Arrival (DOA) estimation of wideband sources by refining the initial estimates and posing the super‐resolution theory in a non‐convex optimization problem. A gradient‐projection method is conducted for the accurate estimation of DOAs. The proposed method can be performed by any non‐uniform linear array with no need for any focusing matrices. Moreover, a greedy search algorithm is employed to obtain initial estimates for super‐resolution implementation. Numerical simulations show the outstanding accuracy of the proposed method and more robustness to noise compared to some well‐known methods. It is also more effective for DOA estimation of adjacent sources.

Gridless wideband DOA estimation in nonuniform noise with increased DOFs

This paper presents gridless schemes for direction finding of wideband sources using sparse array with nonuniform noise. According to the frequencies relationship, we obtain multiple equivalent scaled difference coarrays, which are combined later to formulate synthetic virtual array when sources share the same normalized power spectrum in different subbands. After treating the term affected by nonuniform noise as hole, an atomic norm optimization problem to recover the noise-free signal of interpolated synthetic uniform linear array (ULA) is designed. We analyze the estimation error distribution of the noise-independent terms in synthetic virtual array and based on this, impose a constraint to avoid tuning process and effect of noise. Furthermore, it extremely increases the number of detectable sources, even making it possible to exceed the degree of freedoms of difference coarray. For the general case when sources have arbitrary powers, a multi-snapshot atomic norm optimization problem is formulated, where signal from scaled coarrays is considered as partial observation of synthetic ULA for different snapshots. Similarly, a newly constructed constraint is added, with which most of the above advantages are sustained. Besides, we give the semidefinite programming form and the Cramer-Rao bounds. The superiority of the proposed algorithms is demonstrated by simulations.

Scalability of Large-Scale Photonic Integrated Circuits

To keep up with the growing bandwidth demands, photonic integrated circuits (PICs) have been widely employed in various application scenarios where high capacity and high-bandwidth-density interconnects are required. However, it is challenging to scale the PICs toward future petabit per second capacity requirements. We study the scalability bottlenecks of PICs in terms of guiding materials, dense integration approaches, wide-band optical sources, and high-efficiency tunable and modulation devices. We also look for possible solutions to address these challenges. In the end, we provide a perspective on future PIC development. Moore’s law for integrated photonics may last for a much shorter time than that in the microelectronics industry, requiring significant innovations and technological breakthroughs in PIC research.

Lipid droplet monolayer protein binding and complexation.

The mechanisms by which the lipid droplet membrane contributes to the regulation of lipolysis remains a key unknown in our efforts to understand and treat metabolic disorders. We developed artificial lipid droplets (aLDs), confocal imaging analysis, and four-color fluorescence cross-correlation spectroscopy (FCCS) to reveal the lipid and protein behaviors correlated with triglyceride storage and mobilization. Confocal microscopy was used to assess the competitive binding and stability of lipolysis-associated proteins on coverslip-adhered aLDs caps. The focal plane was set to a few microns above the widest part of a cap and the bound protein densities were observed versus time. We observed the association of perilipin 5 (PLIN5) and alpha beta hydrolase domain containing protein 5 (ABHD5) to the aLD caps with binding rates and saturation values dependent on the solution protein concentrations. In our cost effective, four-color FCCS, the excitation wavelengths were chosen from a single, wide-band laser source and spectral fitting of the emitted light revealed the interactions for up to four fluorophores simultaneously. The fluorescence emission was dispersed onto a sCMOS or EMCCD camera at 10 kHz for spectral fitting of each fluorophore's intensity vs time. The auto- and cross-correlations revealed the diffusion rates and binding partners in complex environments. In particular, we observed the ligand-stimulated association between ABHD5 and adipose triglyceride lipase (ATGL/PNPLA2) coincident with the dissociation of ABHD5 from PLIN5 on the aLD membrane. These studies will provide further understanding of how lipolysis is regulated via protein interactions with the lipid droplet membrane.

Quantum wavelength-division-multiplexing and multiple-access communication systems and networks: Global and unified approach

The march towards successful global quantum internet requires introducing all-quantum networks and signal processing techniques. In this paper, we develop and discuss methods for various wavelength-division-multiplexing and multiple-access (WDM) communication systems and networks in fully quantum mechanical terms to obtain all-quantum WDM (QWDM) systems and networks. We begin the paper with a detailed discussion on various possible narrow-band and wideband sources of light signals used in typical WDM systems, such as coherent, number, and Poissonian mixed states. After introducing a generic and fully quantum mechanical WDM network, we develop methodologies for obtaining the necessary mathematical evolutions through wavelength distributors such as arrayed-waveguide-grating multiplexers and demultiplexers, and wavelength-sensitive and -insensitive broadcasting star couplers. In particular, using the methodologies introduced, one can use the results to obtain a complete and exact expression for any evolved pure quantum light signal through a typical WDM network using the aforementioned optical components. To test the validity and robustness of our mathematical expression for the evolved QWDM light signals, we use two opposing and extreme signals, namely, coherent state and number state, as inputs to various WDM communication and network systems and architecture. The methodologies and the required mathematical QWDM models introduced here can be extended to any fully quantum network architecture deemed necessary in a future global quantum internet, e.g., fiber to the home, Lambdanet-based broadcast WDM networks, and quantum routers based on a waveguide grating router.

Joint angular-frequency distribution estimation via spatial-temporal sparse sampling and low-rank matrix recovery

This paper is committed to the joint angular-frequency distribution (JAFD) estimation for incoherently distributed wideband (IDW) sources by using spatial-temporal sparse sampling (STSS). The STSS increases dramatically the degrees of freedom (DOFs) of the measure system, and can solve the ambiguity problem between angular and frequency parameters. Then, it is observed that the discrete representation of the JAFD gives rise to a helpful low-rank matrix. To estimate the JAFD for IDW sources, a rank minimization problem is further formulated as the modified Schatten-p norm minimization (MSpNM) problem, which can be resolved efficiently by the accelerated iterative singular value thresholding algorithm (AISVTA). Compared with traditional methods based on spatial and temporal Nyquist sampling (STNS), the proposed method based on STSS reduces the sampling rate requirement on hardware and provides better JAFD estimation precision. Experiment simulations indicate its effectiveness and confirm the superior performance of the proposed method based on STSS.

Joint DOA tracking and spectral signature estimation of wideband sources using a multi-spectral TBD-CPHD filter

In this paper, a novel method for direction of arrival (DOA) tracking of multiple unknown time-varying number of wideband emitters is presented using a random finite set (RFS) framework. This method combines multiple narrowband covariance-based measurements to form a wideband cardinalized probability hypothesis density (CPHD) filter using the parallel combination (PC) Lemma generally used in multisensor fusion. By doing this, each narrowband frequency bin acts as a separate virtual spectral sensor. The covariance-based measurements, represented by complex Wishart random matrices, also allow the method to have a track-before-detect (TBD) property, which has shown to be advantageous in very low signal-to-noise ratios (SNR). Furthermore, the proposed method can simultaneously monitor the spectrum of the environment and extract the spectral characteristics of the active sources, i.e. can work as some sort of cognitive radio (CR). The suggested algorithm is implemented using an auxiliary particle filter. The simulation results and the comparison with the known state-of-the-art approaches confirm the superiority of the proposed method in negative SNR scenarios and low number of snapshots.

100-MW-Level Experiments of a Gyromagnetic Nonlinear Transmission Line System

The wideband high-power microwave systems have the advantages of wide energy spectrum, electron beam independence, compactness, and low cost. The gyromagnetic nonlinear transmission line (GNLTL) has drawn much attention for its potential as a novel solid-state, frequency-agile, and compact wideband source. The working mechanism of GNLTL is different from that of the traditional electric vacuum tubes, and the strong dispersion and nonlinear characteristics make it difficult to be accurately theoretically calculated and simulated. In this article, a 100-MW-level GNLTL system based on a Tesla-type driver was designed and constructed. A series of test experiments were then carried out to investigate the effects of different configurations, including delay line length, ferrite cores’ assembly orientation, transmission line length, bias magnetic field magnitude, and excitation voltage. The changing laws of the key parameters of the output microwaves including the peak power, modulation depth, center frequency, and percentage band are summarized and the underlying physical mechanisms are analyzed. The results may be instructive for the predesign of GNLTLs, especially for the devices operating at high power. In addition, a multiple center frequency points’ phenomenon was discovered in the output signal, which may bring new application possibilities for GNLTL.