Multiple Signal Classification Imaging Research Articles

Integrated MUSIC array for high-precision damage diagnosis in complex composite structures

Guided Wave (GW)-based Multiple Signal Classification (MUSIC) damage imaging presents several advantages, such as high resolution, which makes it a promising technique for localizing damage in composite structures. However, the application of this technology in aircraft is confronted with various challenges. The variability in performance of MUSIC array sensors is attributed to material and manufacturing process dispersion. Additionally, the conventional wiring of MUSIC array sensors adds considerable weight and is not compatible with complex structural configurations. Furthermore, within intricate configurations, the attenuation of scattering signals induced by structural damage impacts the accuracy of imaging. Moreover, the manual and individual placement of sensors on structures, along with structural anisotropy, may introduce phase errors in the signals detected by MUSIC array sensors. This can lead to a reduction in the accuracy of MUSIC imaging and result in compromised long-term sensor reliability. This paper proposes a high-precision integrated MUSIC array for the diagnosis of complex composite damage. This approach aims to address the challenges related to damage imaging in materials with complex structures. Impedance curve screening and surface-mount co-curing technology are utilized to manage the performance variation of MUSIC array sensors, enhance layout uniformity, and improve long-term stability. Subsequently, a focus compensation algorithm is proposed within the integrated MUSIC design to enhance precision, reduce weight, and adapt to complex structures. The effectiveness of the proposed method is confirmed through experimental validation on an actual complex composite wing box segment, demonstrating a maximum error of 2 cm in locating impact damage.

A tailor-made cylindrical concrete implantable module for damage imaging in plate-like concrete structures

In this research, a tailor-made cylindrical concrete implantable module (CCIM) was proposed for damage imaging in concrete structures. The CCIM can be directly implanted into inspected structure to transmit and receive probing stress waves, which allows conveniently removing and updating CCIM when devices failed to work. Moreover, a CCIM-based multiple signal classification (MUSIC) algorithm is proposed to realize two-dimensional damage visualization. Based on meso-level finite element simulation, considering concrete as a three-phase composite material, the stress wave propagation characteristics can be revealed and the effectiveness of CCIM-based MUSIC imaging method has been investigated. To verify the proposed method experimentally, a pair of CCIMs were fabricated and implanted into two concrete specimens with different configurations. The results could effectively pinpoint damage location within inspected area. The proposed hardware and algorithm has great potential to overcome the disadvantage of short service period and could be applied for damaging imaging in concrete structures.

Application of MUSIC algorithm for a fast identification of small perfectly conducting cracks in limited-aperture inverse scattering problem

In this study, we investigate MUltiple SIgnal Classification (MUSIC) operated at a fixed frequency for identifying the locations of short, linear perfectly conducting cracks in limited-aperture inverse scattering problem. At present, the so-called multi-static response (MSR) matrix whose elements are measured far-field pattern data is neither symmetric nor Hermitian, a projection operator onto the noise subspace cannot be defined using the conventional method, so the imaging function cannot be designed. Motivated by this fact, we first propose a novel MUSIC imaging function in limited-aperture inverse scattering problem. This is based on the asymptotic expansion formula for far-field patterns in the presence of small cracks and the structure of singular vectors associated with nonzero singular values of the MSR matrix. Next, the new imaging function was analyzed by establishing a relationship with an infinite series of the Bessel function of the integer order of the first kind and ranges of incident and observation directions. We then observe some properties of MUSIC in limited-aperture problems and show that the proposed imaging function is a generalization of full- and limited-view problems. We finally validate the feasibility and limitation of the proposed MUSIC imaging function through numerical simulation results using synthetic and real data.

A novel study on the MUSIC-type imaging of small electromagnetic inhomogeneities in the limited-aperture inverse scattering problem

We apply MUltiple SIgnal Classification (MUSIC) algorithm for the location reconstruction of a set of two-dimensional circle-like small inhomogeneities in the limited-aperture inverse scattering problem. Compared with the full- or limited-view inverse scattering problem, the collected multi-static response (MSR) matrix is no more symmetric (thus not Hermitian), and therefore, it is difficult to define the projection operator onto the noise subspace through the traditional approach. With the help of an asymptotic expansion formula in the presence of small inhomogeneities and the structure of the MSR-matrix singular vector associated with nonzero singular values, we define an alternative projection operator onto the noise subspace and the corresponding MUSIC imaging function. To demonstrate the feasibility of the designed MUSIC, we show that the imaging function can be expressed by an infinite series of integer-order Bessel functions of the first kind and the range of incident and observation directions. Furthermore, we identify that the main factors of the imaging function for the permittivity and permeability contrast cases are the Bessel function of order zero and one, respectively. This further implies that the imaging performance significantly depends on the range of incident and observation directions; peaks of large magnitudes appear at the location of inhomogeneities for permittivity contrast case, and for the permeability contrast case, peaks of large magnitudes appear at the location of inhomogeneities when the range of such directions is narrow, while two peaks of large magnitudes appear in the neighborhood of the location of inhomogeneities when the range is wide enough. The numerical simulation results via noise-corrupted synthetic data also show that the designed MUSIC algorithm can address both permittivity and permeability contrast cases.

A novel multi-site damage localization method based on near-field signal subspace fitting using uniform linear sensor array

Damage diagnose imaging methods based on guided waves have been widely developed to depict the position and area of damage in structural health monitoring (SHM). Among them, compact sensor array based imaging methods have been gradually applied with high accuracy, such as phased array imaging, spatial filter imaging, multiple signal classification imaging and so on. However, when the multi-site damage appears nearly, the performance of these methods usually degrades. On one hand, limited to the array aperture, traditional methods cannot distinguish adjacent damage sites. On another hand, some subspace decomposition based methods also fail, suffering from the correlation between scattered array signals from different damage sites. To realize localization of multi-site damage, a novel near-field signal subspace fitting based multi-site damage localization method is proposed in this paper. This method constructs the cost function, which describe the equivalence relation between the signal subspace and array manifold matrix. Then localization of multi-site damage could be realized through multidimensional search for the optimization of cost function. The proposed method is verified on the aluminum panel with 3 damage sites. Experimental results show that the proposed method can realize multi-site damage localization with the angle errors less than 4° and the distance errors less than 35 mm.

Far-Field Sub-Wavelength Imaging of Two-Dimensional Extended Target Aided By Compact Planar Resonant Structures

Two kinds of compact planar electrical resonant structures (PERSs) are proposed as the solution to realize far-field sub-wavelength imaging of extended target. The proposed structures have their advantages in low profile, compact size, and electrical coupling property. The conversion between evanescent and propagation waves of the two structures enables the sub-wavelength information to be carried to far-field. The first PERS consists of periodically distributed spiral resonators. With the help of background Green's function, sub-wavelength images of two-dimensional extended target with the resolutions of λ/11 from simulation and λ/7 from experiment are reconstructed in the far-field by multiple signal classification imaging method. The second PERS similarly consists of spiral resonators, which operate at different frequencies. Image of an extended target with a resolution of λ/17 from experiment is reconstructed from the spectra received in the far-field, without the use of the background Green's function. Both simulations and experiments are performed to validate the proposed structures. The sub-wavelength imaging results show that the proposed PERSs can be widely applied in new super-resolution imaging systems.

Far-field super-resolution imaging based on wideband stereo-metalens

The resolution of traditional far-field imaging system is generally restricted by half of wavelength of incident light due to the diffraction limit. The reason is that evanescent waves carrying subwavelength information cannot propagate in the far-field and make no contribution to the imaging. To realize the far-field super-resolution imaging, the imaging system should be able to collect both propagation and evanescent waves. Many ideas were presented to provide feasible alternatives but with narrow frequency band. In this paper, a wideband metalens is proposed to realize far-field super-resolution based on stereometamaterials. A typical model of stereometamaterials is studied, which consist of a stack of two identical spiral resonators in each cell, with various twist angles. For each case, there are two observable resonances (-and +), obviously. The phenomenon can be explained as the plasmon hybridization between the two resonators due to their close proximity. The case with a twist angle of 90 is chosen as the basic cell to constitute the stereo-metalens (S-ML). The last S-ML can work in a frequency range from 1.06 to 1.53 GHz, which is much wider than the planar-metalens. Simulations of near-and far-field spectra are conducted to validate the conversion between evanescent waves and propagation waves. Then with the help of antennas in the far-field to receive the information, sub-wavelength image can be reconstructed. The simulations in frequency-and time-domain are performed to verify the super-resolution characteristics of the S-ML. In frequency-domain, an imaging simulation of L-shaped extended target is combined with multiple signal classification imaging method. The resolution defined by full width at half maximum is 19 mm, corresponding to /12. For comparison, a similar simulation without the S-ML is performed, indicating a resolution of 1.5. It shows the ability of the S-ML to enhance the imaging resolution. In time-domain, by using time reversal technique, the spatial super-resolution characteristic of the S-ML is validated. Compared with the planar-metalens, the S-ML has good spatial super-resolution characteristic. All results show that the S-ML has a good potential application in imaging.

Space-time MUSIC imaging of EMI sensing data and a subspace partition study

To localize sources in electromagnetic induction (EMI) sensing, we propose a space-time MUltiple SIgnal Classification (MUSIC) imaging approach. Under the EMI physical model, the approach is established upon a receiver array-based spatial and temporal response matrix. In contrast to the multi-static response matrix-based MUSIC imaging approach that requires a sufficient number of receivers and transmitters, the new imaging scheme relaxes the condition on a large number of transmitters and thus becomes applicable to a wide range of EMI sensing systems. We also investigate the issue of forming a noise subspace that is essential to the MUSIC performance. Our theoretic analysis indicates that the choice of an underestimated noise subspace is appropriate for the imaging. Thus it implies, when doing a subspace partition required in the MUSIC, that a difficult task of exactly distinguishing signal from noise eigenvalues can be eased greatly in a practical eigenvalue distribution map. The technique is evaluated through the synthetic and real data. The results show that the space-time MUSIC can be used to detect sources with an EMI system consisting of multiple receivers but a few transmitters. As predicted from the theoretical analysis, the tests show that the MUSIC-source locations are robust to under-estimates of the dimension of the noise subspace.

Lamb wave-based subwavelength damage imaging using the DORT-MUSIC technique in metallic plates

A Lamb wave-based, subwavelength imaging algorithm is developed for damage imaging in a metallic plate based on a decomposition of the time-reversal operator method together with a multiple signal classification imaging condition in the space-frequency domain. In this study, a hybrid non-contact inspection system was proposed to image damage in an aluminum plate using a piezoelectric linear array for actuation and a laser Doppler vibrometer line-scan perpendicular to the piezoelectric array for sensing. The physics of incident waves, reflection, and reflected waves that underlie the transfer matrix in the decomposition of the time-reversal operator method is mathematically formulated in the context of guided waves based on the first-order Born approximation. Singular value decomposition is then employed to decompose the experimentally measured transfer matrix into three matrices, detailing the incident wave propagation from the linear actuator array, reflection from the damage, and followed by reflected waves toward the linear sensing array for each small damage. The singular value decomposition and multiple signal classification imaging condition enable providing insight on both the damage “reflectivity” and detecting damage smaller than a wavelength (subwavelength). With the flexibility of this inspection system, a considerably large area can be imaged using lower frequency Lamb waves with rapid line-scans. The experimental results showed that the hardware system with a signal processing tools such as the decomposition of the time-reversal operator with multiple signal classification (time-reversal with multiple signal classification) imaging technique can provide robust, highly accurate imaging results as well as providing damage reflectivity estimation with unknown material properties.

A necessary condition for applying MUSIC algorithm in limited-view inverse scattering problem

Throughout various results of numerical simulations, it is well-known that MUltiple SIgnal Classification (MUSIC) algorithm can be applied in the limited-view inverse scattering problems. However, the application is somehow heuristic. In this contribution, we identify a necessary condition of MUSIC for imaging of collection of small, perfectly conducting cracks. This is based on the fact that MUSIC imaging functional can be represented as an infinite series of Bessel function of integer order of the first kind. Numerical experiments from noisy synthetic data supports our investigation.

Analysis of MUSIC-type imaging functional for single, thin electromagnetic inhomogeneity in limited-view inverse scattering problem

This study analyzes the well-known MUltiple SIgnal Classification (MUSIC) algorithm to identify unknown support of thin penetrable electromagnetic inhomogeneity from scattered field data collected within the so-called multi-static response matrix in limited-view inverse scattering problems. The mathematical theories of MUSIC are partially discovered, e.g., in the full-view problem, for an unknown target of dielectric contrast or a perfectly conducting crack with the Dirichlet boundary condition (Transverse Magnetic–TM polarization) and so on. Hence, we perform further research to analyze the MUSIC-type imaging functional and to certify some well-known but theoretically unexplained phenomena. For this purpose, we establish a relationship between the MUSIC imaging functional and an infinite series of Bessel functions of integer order of the first kind. This relationship is based on the rigorous asymptotic expansion formula in the existence of a thin inhomogeneity with a smooth supporting curve. Various results of numerical simulation are presented in order to support the identified structure of MUSIC. Although a priori information of the target is needed, we suggest a least condition of range of incident and observation directions to apply MUSIC in the limited-view problem.

Ultrasonic broadband time-reversal with multiple signal classification imaging using full matrix capture

Ultrasonic broadband time-reversal with multiple signal classification imaging using full matrix capture

Imaging through random multiple scattering media using integration of propagation and array signal processing

Imaging of objects through complex environment is important in several applications, including imaging of hidden objects in obscuring media such as atmospheric and ocean turbulence, rough ocean surfaces, rain, fog, snow, and biological tissues. These media are often randomly varying in space and time, and statistical treatments are necessary to obtain images with useful spatial and temporal resolutions. In recent years, there has been increasing interest in using signal processing and correlation techniques to improve resolutions and to distinguish images from clutter. This paper presents several imaging techniques for objects in the presence of random media. Time-reversal MUSIC (multiple signal classification) imaging has excellent resolution when multiple scattering is small or moderate. Modified beamformer imaging has moderately high resolution even at large multiple scattering. We also include time reversal (TR) and synthetic aperture radar (SAR) imaging for comparison. The technique involves stochastic Green's function and mutual coherence function (MCF), eigenvectors of time-reversal matrix and pseudo spectrum. Numerical examples are given to show the effectiveness of these imaging techniques.

Time-Reversal MUSIC Imaging with Time-Domain Gating Technique

A time-reversal (TR) approach with multiple signal classification (MUSIC) provides super-resolution for detection and localization using multistatic data collected from an array antenna system. The theory of TR-MUSIC assumes that the number of antenna elements is greater than that of scatterers (targets). Furthermore, it requires many sets of frequency-domain data (snapshots) in seriously noisy environments. Unfortunately, these conditions are not practical for real environments due to the restriction of a reasonable antenna structure as well as limited measurement time. We propose an approach that treats both noise reduction and relaxation of the transceiver restriction by using a time-domain gating technique accompanied with the Fourier transform before applying the TR-MUSIC imaging algorithm. Instead of utilizing the conventional multistatic data matrix (MDM), we employ a modified MDM obtained from the gating technique. The resulting imaging functions yield more reliable images with only a few snapshots regardless of the limitation of the antenna arrays.

RESOLUTION THRESHOLD ANALYSIS OF MUSIC ALGORITHM IN RADAR RANGE IMAGING

Super-resolution algorithms used in radar imaging, e.g., MUltiple SIgnal Classification (MUSIC), can help us to get much higher resolution image beyond what is limited by the signal's bandwidth. We focus on MUSIC imaging algorithm in the paper and investigate the uniqueness and effectiveness conditions of the MUSIC algorithm when used in 1-D radar range imaging. Unlike conventional radar resolution analysis, we introduced the concept of resolution threshold from Direction of Arrival (DOA) into the MUSIC radar range imaging, we derive an approximate expression of theoretical resolution threshold for 1-D MUSIC imaging algorithm through the approach of asymptotic and statistical analysis to the null spectrum based on the perturbation theory of algebra and matrix theories. Monte Carlo simulations are presented to verify the work.

Krylov methods in time‐reversal imaging by multiple‐signal‐classification.

Multiple signal classification (MUSIC) has been used to form images and identify sound sources since 1986 [R. O. Schmidt, “Multiple emitter location and signal parameter estimation,” IEEE Trans. Antennas Propag., AP‐34, 276–280 (1986)]. In active sonar imaging of point targets, the MUSIC method can be used to estimate the range of the time‐reversal operator. In this context, the method is related to the decomposition of the time‐reversal operator method. Typical implementations of these methods utilize measurements of the entire time‐reversal operator, and require computations of its eigenvalues and eigenvectors. By contrast, we show that Krylov iterative methods can be used to perform MUSIC imaging with relatively few acoustic excitations. Furthermore, by using the Lanczos technique, no eigenvalues or eigenvectors need be computed. Rather, an orthonormal basis for the range space of the time‐reversal operator can be constructed directly from the received data. Most of the necessary computing is performed by the array itself, performing as a kind of “analog computer.” Finally, we show that useful images can be formed from one iteration to the next, while the data are being collected.

MUSIC imaging applied to total internal reflection tomography

This paper applies the multiple signal classification (MUSIC) imaging method to determine the locations of a collection of small anisotropic spherical scatterers in the framework of total internal reflection tomography. Multiple scattering between scatterers is considered, and the inverse scattering problem is nonlinear, which, however, is solved by the proposed fast analytical approach where no associated forward problem is iteratively evaluated. The paper also discusses the role of propagating and evanescent waves, the polarization of incidence waves, separation of scatterers from the surface of the substrate, and the level of noise on the resolution of imaging.