Fredrik Lingvall

Synthetic aperture imaging using sources with finite aperture: Deconvolution of the spatial impulse response

A method for ultrasonic synthetic aperture imaging using finite-sized transducers is introduced that is based on a compact, linear, discrete model of the ultrasonic measurement system developed using matrix formalism. Using this model a time-domain algorithm for deconvolution of the transducers spatial impulse responses (SIRs) is developed that is based on a minimum mean square error (MMSE) criterion. The algorithm takes the form of a spatiotemporal filter that compensates for the SIRs associated with a finite-sized transducer at every point of the processed image. A major advantage of the proposed method is that it can be used for any transducer, provided that its associated SIRs are known. This is in contrast to the synthetic aperture focusing technique (SAFT), which treats the transducer as a point source. The performance of the method is evaluated with simulations and experiments, performed in water using a linear phased array. The results obtained using the proposed method are compared to those obtained with a classical time-domain SAFT algorithm. For a finite aperture source, it is clearly shown that the resolution obtained using the proposed method is superior to that obtained using the SAFT algorithm.

Automatic detecting and classifying defects during Eddy current inspection of riveted lap-joints

This article presents a novel method for automatic detection and classification of cracks located in the second lower layer of the aircraft lap-joints during Eddy Current (EC) inspection. The cracks originating from the rivet holes were detected using a tailor-made deep penetrating EC probe. The proposed method consists of three steps: pre-processing, feature extraction and classification. The pre-processing, performed before the feature extraction included median filtering, rotation and de-biasing of the EC patterns. The rotation of the patterns was performed so that energy of the responses to the rivets was maximized along the quadrature direction, while the defect responses were maximized in the in-phase direction in the impedance plane. Feature extraction was then performed using four different methods: discrete wavelet transform, Fourier descriptors, principal component analysis (PCA) and block mean values. The classification was performed using a standard multi-layer perceptron (MLP) neural network. All the pre-processing methods showed similar classification performance on the used data set, but the PCA method compressed the data best.

On Time-Domain Model-Based Ultrasonic Array Imaging

This paper treats time-domain model-based Bayesian image reconstruction for ultrasonic array imaging and, in particular, two reconstruction methods are presented. These two methods arc based on a linear model of the array imaging system and they perform compensation in both the spatial and temporal domains using a minimum mean squared error (MMSE) criterion and a maximum a posteriori MAP) estimation approach, respectively. The presented estimators perform compensation for both the electrical and acoustical wave propagation effects for the ultrasonic array system at hand. The estimators also take uncertainties into account, and, by the incorporation of proper prior knowledge, high-contrast superresolution reconstruction results are obtained. The novel nonlinear MAP estimator constrains the scattering amplitudes to be positive, which applies in applications where the scatterers have higher acoustic impedance than the surrounding medium. The linear MMSE and nonlinear MAP estimators are compared to the traditional delay-and-sum (DAS) beamformer with respect to both resolution and signal-to-noise ratio. The algorithms are compared using both simulated and measured data. The results show that the model-based methods can successfully compensate for both side-lobes and grating lobes, and they have a superior temporal and lateral resolution compared to DAS beamforming. The ability of the nonlinear MAP estimator to suppress noise is also superior compared to both the linear MMSE estimator and the DAS beamformer.

Optimized algorithm for synthetic aperture imaging

We present a novel synthetic aperture imaging algorithm based on concepts used in synthetic aperture radar (SAR) and sonar (SAS). The algorithm, based on a convolution model of the imaging system developed in the frequency domain, accounts for the beam-pattern of the finite sized transducer used in the synthetic aperture. A 2D Fourier transform is used for the calculation of the 2D spectrum of the ultrasonic data. The spectrum is then interpolated to convert the polar coordinate system used for the acquisition of ultrasonic signals to rectangular coordinates. After windowing, the transformed spectrum is subjected to the 2D inverse Fourier transform to get the time domain image again. Performance of the proposed algorithm and the classical time-domain SAFT (synthetic aperture focusing technique) are compared using both simulated and real ultrasonic data.

Multiple-point statistical room correction for audio reproduction: minimum mean squared error correction filtering.

This paper treats the problem of correction of loudspeaker and room responses using a single source. The objective is to obtain a linear correction filter, which is robust with respect to listener movement within a predefined region-of-interest. The correction filter is based on estimated impulse responses, obtained at several positions, and a linear minimum mean squared error criteria. The impulse responses are estimated using a Bayesian approach that takes both model errors and measurement noise into account, which results in reliable impulse response estimates and a measure of the estimation errors. The correction filter is then constructed by using information from both the estimated impulse response coefficients and their associated estimation errors. Furthermore, in the optimization criteria a time-dependent reflection filter is introduced, which attenuates the high frequency parts of the reflected responses, that is, the parts of the responses that cannot be compensated with a single source system. The resulting correction filter is shown to significantly improve both the temporal and spectral properties of the responses compared to the uncorrected system, and, furthermore, the obtained correction filter has a low level of pre-ringing.

Compensating transducer diffraction effects in synthetic aperture imaging for immersed solids

One of the fundamental requirements for the successful application of the classical synthetic aperture focusing technique (SAFT) is the use of a transducer that emits spherical (cylindrical) waves. For a planar transducer, the performance of the SAFT algorithm will deteriorate if its active area becomes too large comparing to the wavelength. This is due to the spatial impulse responses (SIRs) associated with the transducer that no longer resemble Dirac functions since the emitted waves is not spherical. Therefore, to achieve a high resolution or finite-sized transducers, the SIRs must be taken into consideration. Here, we propose a method that is based on a discrete linear model of the imaging system. The method uses a spatio-temporal deconvolution technique designed to minimize the mean squared reconstruction error of the imaging system. To demonstrate the performance of the proposed method we present experiments using a phased array for the inspection of a copper specimen. The results obtained using the deconvolution method for finite apertures are compared to those obtained with a time-domain SAFT algorithm and a focused phased array.

Statistically motivated design of input signals for modern ultrasonic array systems.

Modern array systems allow for excitation of separate elements using arbitrary wave forms. This is utilized in pulse compression and coded excitation techniques to improve the imaging performance. Such techniques are however somewhat inflexible since they use predefined excitation schemes. This paper presents a more flexible method for optimizing the input signals to an ultrasonic array in such a way that the scattering strengths at arbitrarily chosen control points in the insonified object can be estimated with as small an error as possible, measured with a mean squared error criteria. The statistically motivated method is based on a linear model of the array imaging system and the method takes into account both prior information regarding the scattering strengths and measurement errors. The input signals are found by using genetic optimization and are constrained to have finite duration and bounds on the maximum amplitudes. Different constellations of control points, and different signal-to-noise ratios, yield different excitation schemes. The design approach finds multiple selective focal laws when choosing relatively well separated control points and when the control points are closely spaced, the resulting excitations result in more diffuse fields. Because of the flexibility in choosing the control points, the design method will be useful when developing transmission schemes aiming at fast imaging of large image areas using few transmissions.

3B-4 Statistically Motivated Design of Input Signals for Ultrasonic Array Imaging

Modern array systems allow for excitation of separate elements using arbitrary waveforms. This is utilized in pulse compression and coded excitation techniques to improve the imaging performance. Such techniques are however somewhat inflexible since they use predefined excitation schemes. This paper presents a new more flexible method for optimizing the input signals to an ultrasonic array in such way that the scattering strengths at arbitrarily chosen control points in the insonified object can be estimated with as low error as possible, measured with a mean squared error criteria. The statistically motivated method is based on a linear model of the array imaging system where both prior information regarding the scattering strengths and measurement errors are taken into account. The input signals are found by using genetic optimization and are constrained to have finite duration and bounds on the maximum amplitudes. Different constellations of control points yield different excitation schemes. The design approach finds multiple selective focal laws when choosing relatively well separated control points and when the control points are closely spaced, the resulting excitations results in more diffuse fields, reminiscent to those resulting from coded excitation. Because of the flexibility in choosing the control points, the design method will be useful when developing transmission schemes aiming at fast imaging of large image areas using few transmissions

High resolution ultrasonic array imaging using positivity constraints on the scattering amplitudes

In this paper a beamforming method for ultrasonic array imaging is presented that performs com- pensation in both the spatial and temporal domain based on a maximum a posteriori (MAP) estimation approach. The presented MAP estimator performs a regularized inversion of the propagation operator for the ultrasonic array system at hand by constraining the scattering amplitudes to be positive which applies in applications where the scatterers have higher acoustic impedance than the surrounding medium. The novel non-linear MAP beamformer is compared to a linear beamformer based on a minimum mean squared error (MMSE) criteria as well as to the traditional delay-and-sum (DAS) beamformer with respect to both resolution and signal- to-noise ratio. The algorithms are compared using both simulated and measured data. The results show that the non-linear MAP beamformer has superior temporal and lateral resolution compared to DAS beamforming and the ability to suppress noise is better for the non-linear MAP beamformer compared to both the linear MMSE beamformer and the DAS beamformer.

Two‐dimensional synthetic focusing using large apertures—Deconvolution of the spatial impulse response

The synthetic aperture focusing technique (SAFT) has been used successfully in both medical and nondestructive evaluation (NDE) applications of ultrasound. Transducer size is an important issue when implementing SAFT algorithms. The classical SAFT method is based on the assumption that a point source is used for emitting ultrasonic waves, which means in practice that the transducer aperture is so small compared to the wavelength that it emits spherical waves. If the transducer aperture is large its spatial impulse response (SIR) significantly differs from a Dirac pulse and nonspherical waves will be generated. Therefore, to successfully perform synthetic focusing using large apertures, the transducer’s SIR must be taken into account. A new method for compensating transducer SIR in synthetic focusing is presented in the paper. The method employs a stochastic, time‐domain Wiener filtering technique for two‐dimensional synthetic focusing. Results of the experiments performed in water using a linear phased array are presented to demonstrate the performance of the proposed method. The use of an array enabled altering the aperture without changing the electrical characteristics of the whole system. The results obtained using the proposed technique for finite apertures are compared to those obtained with a classical SAFT algorithm.