Multiple Signal Characterization Research Articles

A novel dual-radar fusion method for improving the cross-range resolution of ISAR imagery

ABSTRACT For the intelligent crossroad with millimetre wave radar, two radars are placed perpendicular to each other to complete the monitoring and identification of vehicles which means the cross-radar can obtain inverse synthetic aperture radar (ISAR) image while the radial radar can not obtain, but the cross-range of a scattering point in ISAR image is equivalent to the radial range of the same point in another radar’s view. Thus, the special placement of radar is utilized to improve cross-range resolution in ISAR image. In this letter, a novel dual-radar fusion method for improving ISAR image cross-range resolution for isolated scattering points on target is proposed. First, the range information of scatters is gathered from radial radar based on multiple signal characterization (MUSIC) algorithm. Then, data interpolation and construction of the modulation function will be completed. Finally, the ISAR image cross-range resolution can be improved by fusing the ISAR image obtained from cross-radar and the modulation function. The effectiveness of the proposed method is validated by simulation and experimental results.

High-resolution range profile reconstruction method for terahertz FMCW radar.

Terahertz (THz) testing, by the frequency modulated continuous wave (FMCW) system, is often hampered by the limited range resolution. Thus, in this paper, a software method is proposed to reconstruct the range profile, yielding significant improvements in range resolution and in signal parameter extraction. Specifically, the multiple signal characterization algorithm is first introduced to indicate a higher-resolution range profile qualitatively and to acquire the echoes' initial values. Then, multiple Gaussian functions are applied to fit those echoes in the whole original range profile and to accurately extract the parameters, including the amplitude, range, and width, of each echo. Finally, with these parameters, the range profile can be more precisely and flexibly reconstructed, facilitating the following detection procedure to a great extent. Both the simulated and the real THz data, acquired by a 150-220 GHz FMCW imager, have been used to demonstrate the superiority and effectiveness of our method, qualitatively and quantitatively.

A Support Vector Machine MUSIC Algorithm

This paper introduces a new Support Vector Machine (SVM) formulation for the direction of arrival (DOA) estimation problem. We establish a theoretical relationship between the Minimum Variance Distortionless Response (MVDR) and the MUltiple SIgnal Characterization (MUSIC) methods. This leads naturally to the derivation of an SVM-MUSIC algorithm, which combines the benefits of subspace methods with those of SVM. Spatially smoothed versions and a recursive form of the algorithms exhibit good performance against coherent signals. We test the method's performance in scenarios with noncoherent and coherent signals, and in small-sample size-situations obtaining an improved performance in comparison with existing standard approaches.

Double multiple signal characterization active large band (D-MUSICAL) for extraction of observable in acoustic tomography

In the ocean, the acoustic propagation is characterized by different arrivals. Each arrival is characterized by its observables: amplitude, arrival time, emission, and reception angles. To achieve ocean acoustic tomography, a method to separate arrivals and extract observables has been developed. Two vertical arrays are used: a source and a receive array. Until now, the double-beamforming algorithm has been used to extract observables. It allows to go from the initial (time–source depth–receiver depth) domain to the beamformed domain (time–source angle–receive angle). This algorithm is efficient thanks to the 3-D domain of estimation but shows resolution limitation in the angle domain. To improve wave separation, we develop and apply a high-resolution algorithm based on MUSIC principle, in the same 3-D domain. The proposed method, called Double-MUSICAL, is the extension on the emission angle of the 2-D MUSIC Acitve Large band method (MUSICAL). Its principle is to separate the recording space onto the two orthogonal signal and noise spaces. We present results on real data recorded in an ultrasonic tank and show that the developed method better detects and separates the first arrivals than double beamforming.

SVD for enhanced explosives detection using NQR

Nuclear Quadrupole Resonance (NQR) is a solid-state radio frequency (RF) spectroscopic technique, allowing the detection of many high explosives and narcotics. Unlike metal detectors and ground penetrating radar (GPR), NQR detectors measure signals that are unique to the explosives, thus can provide a lower false alarm rate. The practical use of NQR is restricted by the inherently low signal-to-noise ratio (SNR) of the observed signals, a problem that is further exacerbated by the presence of strong RF interference (RFI), so a robust detection method is required. Singular value decomposition (SVD) based on Hankel matrix is proposed to detect the NQR signal in this paper. The original signal can be decomposed into the linear superposition of a series of component signals by SVD using Hankel matrix, and the process of constructing the Hankel matrix shows that a component T signal can be produced by averaging the elements on the inverse diagonal of the Ai=σiuiviT. Then an eigendecomposition based spectrum estimator called “Multiple Signal Characterization” (MUSIC) is applied to estimate power spectrum of each component signal, so the RFI and the noise are canceled by using the priori knowledge of the NQR frequency. Finally, an average power detector is applied to detect NQR signal. The result using measured data shows that the proposed method can provide robust NQR detection performance.

High resolution approach for the localization of buried defects in the multi-frequency eddy current imaging of metallic structures

A high resolution approach is proposed to quantitatively estimate the depth of defects buried in planar metallic structures. This approach associates a multiple signal characterization (MUSIC) algorithm with an original eddy current imager. The interactions of the eddy currents and the defects are modelled by a set of virtual magnetic sources propagating in a spherical manner up to the surface of the structure. The defect localization is carried out using the MUSIC algorithm, applied to the multi-frequency observation of the magnetic field distribution at the surface of the structure. Accurate results obtained on simulated and experimental data relative to defects buried down to 5.4 mm in an aluminium layered structure validate the approach.

Coherent-subspace array processing based on wavelet covariance: an application to broad-band, seismo-volcanic signals

SUMMARY Long-Period (LP) and Very-Long-Period (VLP) signals are the most characteristic seismic signature of volcano dynamics, and provide important information about the physical processes occurring in magmatic and hydrothermal systems. These events are usually characterized by sharp spectral peaks, which may span several frequency decades, by emergent onsets, and by a lack of clear S-wave arrivals. These two latter features make both signal detection and location a challenging task. In this paper, we propose a processing procedure based on Continuous Wavelet Transform of multichannel, broad-band data to simultaneously solve the signal detection and location problems. Our method consists of two steps. First, we apply a frequency-dependent threshold to the estimates of the array-averaged WCO in order to locate the time-frequency regions spanned by coherent arrivals. For these data, we then use the time-series of the complex wavelet coefficients for deriving the elements of the spatial Cross-Spectral Matrix. From the eigenstructure of this matrix, we eventually estimate the kinematic signals' parameters using the MUltiple SIgnal Characterization (MUSIC) algorithm. The whole procedure greatly facilitates the detection and location of weak, broad-band signals, in turn avoiding the time-frequency resolution trade-off and frequency leakage effects which affect conventional covariance estimates based upon Windowed Fourier Transform. The method is applied to explosion signals recorded at Stromboli volcano by either a short-period, small aperture antenna, or a large-aperture, broad-band network. The LP (0.2 2 s) of the explosion recordings from the broad-band network. Source locations obtained this way are fully compatible with those retrieved from application of more traditional (and computationally expensive) time-domain techniques, such as the Radial Semblance method.

A comparison of observed and simulated site response in the Rhône valley

Summary Site effects in the city of Sion in the Rhône valley are analysed from weak motion signals recorded on a dense temporary array. We simulate the recorded events with a 3-D finite difference method for frequencies up to 4 Hz using a recently developed velocity model of the Sion basin. Site-to-reference Fourier spectral ratios are computed from 16 local and regional events. All sites exhibit amplification factors of up to 12 between 0.5 and 0.6 Hz, which can be reproduced by the numerical simulations. By rotating the weak motion to directions parallel and perpendicular to the valley axis, we show that this low-frequency amplification is caused by the SH00 and SV0 fundamental modes of 2-D resonance. Additional peaks of amplification can be observed at higher frequencies, with amplification factors of up to 20 at some sites. Application of the high-resolution frequency-wavenumber and the multiple signal characterization method to the vertical component of recorded and simulated signals show that edge-generated surface waves arriving from almost all directions dominate the wavefield at 1.25 and 2.50 Hz. Peak ground velocities computed from the simulated ground motion show interference patterns that depend strongly on the incidence direction, and the computed amplification of peak ground velocities are generally in agreement with the observations. We conclude that the complex 3-D geometry of the basin needs to be considered to evaluate site effects up to at least 2.5 Hz.

Skill Assessment of Resolving Ocean Surface Current Structure Using Compact-Antenna-Style HF Radar and the MUSIC Direction-Finding Algorithm

Abstract A skill analysis of the Multiple Signal Characterization (MUSIC) algorithm used in compact-antenna-style HF radar ocean current radial velocity/bearing determination is performed using simulation. The simulation is based upon three collocated antennas (two cross loops and a monopole with ideal gain patterns) in a geometry similar to the 25-MHz SeaSonde HF radar commercially available from Coastal Ocean Dynamics Applications Radar (CODAR) Ocean Sensors, Palo Alto, California. The simulations consider wind wave/current scenarios of varying complexity to provide insight to the accuracy of surface current retrievals and the inherent limitations of the technique, with a focus on the capabilities of the MUSIC algorithm itself. The influence of second-order scatter, interference, and stationary target scatter are not considered. Simple error reduction techniques are explored and their impacts quantified to aid in operational system configuration and encourage areas of further research. Increases in skill between 55% and 100% using spatial averaging, and between 14% and 33% using temporal averaging, are realized, highlighting the utility of these techniques. When these error-flagging and averaging techniques are employed, individual range cell skill metrics are found to be as high as 0.94 for simple currents at a high signal-to-noise ratio (SNR), while more complex currents achieve a maximum skill metric of 0.72 for the same SNR. These simulations, conducted under ideal conditions, provide insight to understanding the variables, which influence the accuracy of surface currents retrieved using MUSIC.

Decomposition of the time reversal operator applied to subwavelength localization of scatterers

The decomposition of the time reversal operator (DORT method in French) is an ultrasonic detection method based the analysis of the whole pulse echo responses of an array. The eigenvalues and the eigenvectors of the time reversal operator (i.e., singular values and singular vectors of the array response matrix) provides information on localization of scatterers in the insonified medium. Recent experiments shows how DORT can also be used as a characterization method of subwavelength scatterers as cylinders [Minonzio et al., J. Acoust. Soc. Am. accepted May (2004)]. It has been shown that multiple singular values are associated with a single scatterer and that the singular vectors are combinations of the normal modes (monopole, dipole) of vibrations. In this study, interactions between two subwavelength cylinders less than a wavelength apart are described. Multiple scattering affects the singular value distribution. Experiments and calculations have been carried out on nylon and metal cylinders with diameters ranging from 0.07 to 0.2 mm. The central frequency is 1.5 MHz, and the scatterers are 5 cm away from the array. The estimator multiple signal characterization (MUSIC) is used for subwavelength localization of scatterers [Prada et al., J. Acoust. Soc. Am. 114, 235–243 (2003)].

Robust estimation of fetal heart rate variability using doppler ultrasound

This paper presents a new measure of heart rate variability (HRV) that can be estimated using Doppler ultrasound techniques and is robust to variations in the angle of incidence of the ultrasound beam and the measurement noise. This measure employs the multiple signal characterization (MUSIC) algorithm which is a high-resolution method for estimating the frequencies of sinusoidal signals embedded in white noise from short-duration measurements. We show that the product of the square-root of the estimated signal-to-noise ratio (SNR) and the mean-square error of the frequency estimates is independent of the noise level in the signal. Since varying angles of incidence effectively changes the input SNR, this measure of HRV is robust to the input noise as well as the angle of incidence. This paper includes the results of analyzing synthetic and real Doppler ultrasound data that demonstrates the usefulness of the new measure in HRV analysis.

Experimental subwavelength localization of scatterers by decomposition of the time reversal operator interpreted as a covariance matrix.

The D.O.R.T. method (French acronym for Decomposition of the Time Reversal Operator) is an active remote sensing technique using arrays of antennas for the detection and localization of scatterers [Prada et at., J. Acoust. Soc. Am. 99, 2067-2076 (1996)]. The analogy between the time reversal operator and the covariance matrix used for classical sources separation in passive remote sensing [Bienvenu et al., IEEE Trans. ASSP 31, 1235-1247 (1983)] is established. Then, an experiment of subwavelength detection and localization of point-like scatterers with a linear array of transducers is presented. Using classical estimators in reception like Maximum-Likelihood and Multiple Signal Characterization (MUSIC), two point-like scatterers separated by lambda/3 and placed at 100lambda from the array of transducers are resolved. In these experiments, the role of multiple scattering and the existence of additional eigenvectors associated with dipolar and monopolar radiation of each scatterer is discussed.

Site Response, Shallow Shear-Wave Velocity, and Wave Propagation at the San Jose, California, Dense Seismic Array

Ground-motion records from a 52-element dense seismic array near San Jose, California, are analyzed to obtain site response, shallow shear-wave velocity, and plane-wave propagation characteristics. The array, located on the eastern side of the Santa Clara Valley south of the San Francisco Bay, is sited over the Evergreen basin, a 7-km-deep depression with Miocene and younger deposits. Site response values below 4 Hz are up to a factor of 2 greater when larger, regional records are included in the analysis, due to strong surface-wave development within the Santa Clara Valley. The pattern of site amplification is the same, however, with local or regional events. Site amplification increases away from the eastern edge of the Santa Clara Valley, reaching a maximum over the western edge of the Evergreen basin, where the pre-Cenozoic basement shallows rapidly. Amplification then decreases further to the west. This pattern may be caused by lower shallow shear-wave velocities and thicker Quaternary deposits further from the edge of the Santa Clara Valley and generation/trapping of surface waves above the shallowing basement of the western Evergreen basin. Shear-wave velocities from the inversion of site response spectra based on smaller, local earthquakes compare well with those obtained independently from our seismic reflection/refraction measurements. Velocities from the inversion of site spectra that include larger, regional records do not compare well with these measurements. A mix of local and regional events, however, is appropriate for determination of site response to be used in seismic hazard evaluation, since large damaging events would excite both body and surface waves with a wide range in ray parameters. Frequency-wavenumber, plane-wave analysis is used to determine the backazimuth and apparent velocity of coherent phases at the array. Conventional, high-resolution, and multiple signal characterization f-k power spectra and stacked slowness power spectra are compared. These spectra show surface waves generated/scattered at the edges of the Santa Clara Valley and possibly within the valley at the western edge of the Evergreen basin.

Simulation-based evaluations of HF radar ocean current algorithms

A computer simulation is used to analyze errors in high-frequency (HF) radar ocean surface current measurements. Two pointing algorithms used for current extraction, a direction finding approach using MUltiple SIgnal Characterization (MUSIC) developed by Schmidt (1986), and conventional beam forming, are compared in terms of the effect of variations in sea state parameters on current measurement error. The radar system parameters used in the simulation were taken from the University of Michigan's multi-frequency coastal radar (MCR), which operates on four frequencies from 4.8 to 21.8 MHz and employs an eight-element linear phased array for its receive antenna. Results show MUSIC direction finding to be applicable to phased array systems and to have a better sensitivity to sharp current features, but larger random error than traditional beam forming methods. Also, for cases where beam forming errors are dominated by beam width or low signal to noise ratio, results show MUSIC to be a viable alternative to beam forming.

Min-norm interpretations and consistency of MUSIC, MODE and ML

The multiple signal characterization (MUSIC) approach, its generalization to correlated signals known as the method of direction estimation (MODE), and the deterministic maximum likelihood (ML) approach for bearing estimation in array processing are shown to be signal subspace fitting approaches in a minimum norm sense. MODE, for example, is shown to be an approach in which the array manifold is linearly estimated from principal empirical eigenvectors in a minimum weighted Frobenius norm sense. Using the min-norm interpretations, a unified proof for strong consistency of the three approaches is provided for stationary and ergodic signals.

Seismic Wave Slowness-Vector Estimation From Broad-Band Array Data

SUMMARY In this paper, a new procedure, called the coherent-signal-subspace method (CSS), for broad-band multiple-signal detection and slowness-vector estimation is discussed and applied to a surface seismographic array. the major improvements in estimation accuracy and resolution given by the CSS method, which was developed in the fields of radar and sonar, result from the use of extended-frequency components within the data bandwidth and a high-resolution algorithm. the former is made possible through a frequency focusing transformation that for each frequency component corrects for the phase-delay difference between that frequency and a reference frequency ωo. the result is the condensation of a broad frequency band into a narrow band at ωo. the high resolution algorithm used in the CSS method is the MUSIC (multiple signal characterization; Schmidt 1986) algorithm, which is based on the eigen property of the data cross-covariance matrix that the signal phase-delay vectors lie within the subspace spanned by the signal eigenvectors. the frequency transformation improves the singularity of the estimated cross-covariance matrix and the accuracy of the estimated signal eigenvectors at ωo, which are often serious problems in seismic array analysis. Combination of these two features in CSS ensures a superior array performance over the widely used beam steering and minimum-variance (Capon 1969) methods. Approximate methods to estimate the mean and variance of the estimated slowness vector are also presented in this paper. the estimation biases introduced by deterministic arrival-time deviations of array data from a plane wavefront are derived for the single signal case. It is shown that, in the case of a single signal, significant reduction in the estimation bias may be achieved if a large enough reference frequency is used in the CSS method. Finally, with observed and synthetic ground motions, tests are performed to illustrate the utility of CSS in resolving two closely separated signals. In both cases, CSS successfully resolved two separate peaks at almost the correct slowness vectors, while the conventional beam steering and minimum variance estimation methods either failed to resolve the two signals or gave an incorrect slowness estimate.

MUSIC, maximum likelihood, and Cramer-Rao bound: further results and comparisons

The problem of determining the direction-of-arrival of narrowband plane waves using sensor arrays and the related problem of estimating the parameters of superimposed signals from noisy measurements are studied. A number of results have been recently presented by the authors on the statistical performance of the multiple signal characterization (MUSIC) and the maximum likelihood (ML) estimators for the above problems. This work extends those results in several directions. First, it establishes that in the class of weighted MUSIC estimators, the unweighted MUSIC achieves the best performance (i.e. the minimum variance of estimation errors), in large samples. Next, it derives the covariance matrix of the ML estimator and presents detailed analytic studies of the statistical efficiency of MUSIC and ML estimators. These studies include performance comparisons of MUSIC and MLE with each other, as well as with the ultimate performance corresponding to the Cramer-Rao bound. Finally, some numerical examples are given which provide a more quantitative study of performance for the problem of finding two directions with uniform linear sensor arrays.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Array analysis of seismic signals

In this paper we present a method for analyzing seismic signals recorded at an array of seismometers. The method is based on the multiple signal characterization (MUSIC) method. Four important features of this approach are: (1) it has the ability to resolve multiple closely spaced sources, (2) it works with both stationary, and nonstationary signals, (3) it is most sensitive to the strongest sources, and (4) it provides a geometric interpretation of the solution to the direction finding problem. We have developed a numerical algorithm that extends the MUSIC method to nonstationary and correlated signals. We present results using this algorithm to measure directions of arrival and amplitudes of multiple plane waves in a homogeneous medium.

Multiple source DF signal processing: An experimental system

The multiple signal characterization (MUSIC) algorithm is an implementation of the signal subspace approach to compute parameter estimates of multiple point-source signals from the observed voltages received on an array of M antennas. In it, the solution to the multiple source direction finding (DF) problem is provided by the intersection of the signal subspace (obtained from the received data) and the array manifold (obtained via array calibration or prior knowledge of array directional characteristics). The MUSIC algorithm was implemented to experimentally verify the performance of the signal subspace approach to DF under very general scenarios and conditions which are regarded as difficult to impossible in traditional systems. The results of those experiments are described herein. The experimental system consisted of an eight-element antenna array 13 wavelengths in diameter, an eight-channel receiver and digitizer, and a minicomputer with disk storage to process the digitized data. With ideal instrumentation, the MUSIC algorithm provides performance that, as the amount of data collected increases without limit, is asymptotically ideal. However, with finite precision and finite data collection, the performance of even an ideal system can be a sensitive function of source and scenario parameters. Tests demonstrated the resolution of three sources all within one beamwidth (5 \deg ), even when the closer two were spaced less than 0.2 beamwidths. Sources that were polarized differently could be resolved at closer spacings. Experimental DF accuracy was limited by the oncalibrated scattering of source energy from the test range support tower and from the ground. The measured direction of arrival of one source changed by less than 0.01 beamwidths as the other two sources were switched on and off in all combinations. In general, results indicated that all parameters of a source can be measured and the signal waveform can be recovered as well in the presence of other sources less than a beamwidth away.