Synthetic aperture (SA) technique is a novel approach to present day commercial systems and has previously not been used in medical ultrasound imaging. The basic idea of SA is to combine information acquired simultaneously from all directions over a number of emissions and to reconstruct the full image from these data.

The paper presents the multi-element STA (MSTA) method for medical ultrasound imaging. The main difference with the STA approach is the use of a few elements in the transmit mode in contrast to a single element aperture. This allows increasing the system frame rate, decreasing the number of emissions, and provides the best compromise between the penetration depth and lateral resolution. Besides, a modified MSTA is proposed with a corresponding RF signal correction in the receive mode, which accounts for the element directivity property.

In the experiments a 32-element linear transducer array with 0.48 mm inter-element spacing and a burst pulse of 100 ns duration were used. Two elements wide transmission aperture was used to generate an ultrasound wave covering the full image region. The comparison of 2D ultrasound images of a tissue mimicking phantom obtained using the STA and MSTA methods is presented to demonstrate the benefits of the second one.

The paper presents the optimization problem for the multi-element synthetic transmit aperture method (MSTA) in ultrasound imaging applications. The optimal choice of the transmit aperture size is made as a trade-off between the lateral resolution, penetration depth and the frame rate. Results of the analysis obtained by a developed optimization algorithm are presented. The maximum penetration depth and lateral resolution at given depths are chosen as optimization criteria. The results of numerical experiments carried out in MATLAB® using synthetic aperture data of point reflectors obtained by the FIELD II simulation program are presented. The visualization of experimental synthetic aperture data of a tissue mimicking phantom and in vitro measurements of the beef liver performed using the SonixTOUCH Research system are also shown.

Microphone array with minimum variance (MVDR) beamformer is a commonly used method for ambient noise suppression. Unfortunately, the performance of the MVDR beamformer is poor in a real reverberant room due to multipath wave propagation. To overcome this problem, we propose three improvements. Firstly, we propose end-fire microphone array that has been shown to have a better directivity index than the corresponding broadside microphone array. Secondly, we propose the use of unidirectional microphones instead of omnidirectional ones. Thirdly, we propose an adaptation of its adaptive algorithm during the pause of speech, which improves its robustness against the room reverberation and deviation from the optimal receiving direction. The performance of the proposed microphone array was theoretically analyzed using a diffuse noise model. Simulation analysis was performed for combined diffuse and coherent noise using the image model of the reverberant room. Real room tests were conducted using a four-microphone array placed in a small office room. The theoretical analysis and the real room tests showed that the proposed solution considerably improves speech quality.

Beamforming training (BT) is considered as an essential process to accomplish the communications in the millimeter wave (mmWave) band, i.e., 30 ~ 300 GHz. This process aims to find out the best transmit/receive antenna beams to compensate the impairments of the mmWave channel and successfully establish the mmWave link. Typically, the mmWave BT process is highly-time consuming affecting the overall throughput and energy consumption of the mmWave link establishment. In this paper, a machine learning (ML) approach, specifically reinforcement learning (RL), is utilized for enabling the mmWave BT process by modeling it as a multi-armed bandit (MAB) problem with the aim of maximizing the long-term throughput of the constructed mmWave link. Based on this formulation, MAB algorithms such as upper confidence bound (UCB), Thompson sampling (TS), epsilon-greedy (e-greedy), are utilized to address the problem and accomplish the mmWave BT process. Numerical simulations confirm the superior performance of the proposed MAB approach over the existing mmWave BT techniques.

Directional excitation of sound in an aperiodic finite baffle system is analyzed using a method developed earlier in electrostatics. The solution to the corresponding boundary value problem is obtained in the spatial-frequency domain. The acoustic pressure and normal particle velocity distribution in acoustic media can be easily computed by the inverse Fourier transform from their spatial spectra on the baffle plane. The presented method can be used for linear acoustic phased arrays modeling with finite element size and inter-element interactions taken into account. Some illustrative numerical examples presenting the far-field radiation pattern and wave-beam steering are given.

Sound localization problems are usually tackled by the acquisition of data from phased microphone arrays and the application of acoustic holography or beamforming algorithms. However, the number of sensors required to achieve reliable results is often prohibitive, particularly if the frequency range of interest is wide. It is shown that the number of sensors required can be reduced dramatically providing the sound field is time stationary. The use of scanning techniques such as “Scan & Paint” allows for the gathering of data across a sound field in a fast and efficient way, using a single sensor and webcam only. It is also possible to characterize the relative phase field by including an additional static microphone during the acquisition process. This paper presents the theoretical and experimental basis of the proposed method to localise sound sources using only one fixed microphone and one moving acoustic sensor. The accuracy and resolution of the method have been proven to be comparable to large microphone arrays, thus constituting the so called “virtual phased arrays”.

The work presents the results of experimental study on the possibilities of determining the source of an ultrasonic signal in two-dimensional space (distance, horizontal angle). During the research the team used a self-constructed linear array of MEMS microphones. Knowledge in the field of sonar systems was utilized to analyse and design a location system based on a microphone array. Using the above mentioned transducers and broadband ultrasound sources allows a quantitative comparison of estimation of the location of an ultrasonic wave source with the use of broadband modulated signals (modelled on bats' echolocation signals) to be performed. During the laboratory research the team used various signal processing algorithms, which made it possible to select an optimal processing strategy, where the sending signal is known.

Most receiving antenna arrays suffer from the mutual coupling problem between antenna elements, which can critically influence the performance of the array. In this work, a novel and accurate form of compensation matrix is applied to compensate the mutual coupling in a uniform linear array (ULA). This is achieved by applying a new method based on solving a boundary value problem for the whole ULA. In this method, both self and mutual impedances are exploited in an accurate characterization of mutual impedance matrix which results in a perfect mutual coupling compensation method, and hence a very accurate direction of arrival (DOA) estimation. In the new scheme, the compensation ma- trix is obtained by using the relationship between measured voltage and theoretical coupled voltage based on the MOM. Numerical results show that using DOA estimation algorithms to the decoupled voltage obtained by using this method leads to an excellent performance of DOA estimation with higher accuracy and resolution.

Beamforming is an advanced signal processing technique used in sensor arrays for directional signal transmission

or reception. The paper deals with a system based on an ultrasound transmitter and an array of

receivers, to determine the distance to an obstacle by measuring the time of flight and – using the phase

beamforming technique to process the output signals of receivers for finding the direction from which the

reflected signal is received – locates the obstacle. The embedded beam-former interacts with a PID-based

line follower robot to improve performance of the line follower navigation algorithm by detecting and

avoiding obstacles. The PID (proportional-integral-derivative) algorithm is also typically used to control

industrial processes. It calculates the difference between a measured value and a desired set of points, then

attempts to minimize the error by adjusting the output. The overall navigation system combines a PID-based

trajectory follower with a spatial-temporal filter (beamformer) that uses the output of an array of sensors to

extract signals received from an obstacle in a particular direction in order to guide an autonomous vehicle

or a robot along a safe path.

With the advent of massive MIMO and mmWave, Antenna selection is the new frontier in hybrid beamforming employed in 5G base stations. Tele-operators are reworking on the components while upgrading to 5G where the antenna is a last-mile device. The burden on the physical layer not only demands smart and adaptive antennas but also an intelligent antenna selection mechanism to reduce power consumption and improve system capacity while degrading the hardware cost and complexity. This work focuses on reducing the power consumption and finding the optimal number of RF chains for a given millimeter wave massive MIMO system. At first, we investigate the power scaling method for both perfect Channel State Information (CSI) and imperfect CSI where the power is reduced by ��/���� and ��/√���� respectively. We further propose to reduce the power consumption by emphasizing on the subdued resolution of Analog-to-Digital Converters (ADCs) with quantization awareness. The proposed algorithm selects the optimal number of antenna elements based on the resolution of ADCs without compromising on the quality of reception. The performance of the proposed algorithm shows significant improvement when compared with conventional and random antenna selection methods.

An intelligent security model for the big data environment is presented in this paper. The proposed security framework is data sensitive in nature and the level of security offered is defined on the basis of the data secrecy standard. The application area preferred in this work is the healthcare sector where the amount of data generated through the digitization and aggregation of medical equipment’s readings and reports is huge. The handling and processing of this great amount of data has posed a serious challenge to the researchers. The analytical outcomes of the study of this data are further used for the advancement of the medical prognostics and diagnostics. Security and privacy of this data is also a very important aspect in healthcare sector and has been incorporated in the healthcare act of many countries. However, the security level implemented conventionally is of same level to the complete data which not a smart strategy considering the varying level of sensitivity of data. It is inefficient for the data of high sensitivity and redundant for the data of low sensitivity. An intelligent data sensitive security framework is therefore proposed in this paper which provides the security level best suited for the data of given sensitivity. Fuzzy logic decision making technique is used in this work to determine the security level for a respective sensitivity level. Various patient attributes are used to take the intelligent decision about the security level through fuzzy inference system. The effectiveness and the efficacy of the proposed work is verified through the experimental study.

The paper presents the theoretical and experimental study of synthetic transmit aperture (STA) method combined with Golay coded transmission for medical ultrasound imaging applications. The transmission of long waveforms characterized by a particular autocorrelation function allows to increase the total energy of the transmitted signal without increasing the peak pressure. It can also improve signal-to-noise ratio and increase the visualization depth maintaining the ultrasound image resolution.

In the work the 128-element linear transducer array with 0.3 mm pitch excited by the 8 and 16-bits Golay coded sequences as well as a one cycle at nominal frequencies 4 MHz were used. The comparison of 2D ultrasound images of the tissue mimicking phantoms is presented to demonstrate the benefits of coded transmission. The image reconstruction was performed using synthetic STA algorithm with transmit and receive signals correction based on a single element directivity function.

The paper presents an overview of theoretical aspects of ultrasound image reconstruction techniques based on the circular Radon transform inversion. Their potential application in ultrasonography in a similar way as it was successfully done in the x-ray computer tomography is demonstrated. The methods employing Radon transform were previously extensively explored in the synthetic aperture radars, geophysics, and medical imaging using x-ray computer tomography. In this paper the main attention is paid to the ultrasound imaging employing monostatic transmit-receive configuration. Specifically, a single transmit and receive omnidirectional source placed at the same spatial location is used for generation of a wide-band ultrasound pulse and detection of back-scattered waves. The paper presents derivation of the closed-form solution of the CRT inversion algorithms by two different approaches: the range-migration algorithm (RMA) and the deconvolution algorithm (DA). Experimentally determined data of ultrasound phantom obtained using a 32-element 5 MHz linear transducer array with 0.48 mm element pitch and 0.36 mm element width and 5 mm height, excited by a 2 sine cycles burst pulse are used for comparison of images reconstructed by the RMA, DA, and conventional synthetic aperture focusing technique (SAFT). It is demonstrated that both the RMA and SAFT allow better lateral resolution and visualization depth to be achieved as compared to the DA approach. Comparison of the results obtained by the RMA method and the SAFT indicates slight improvement of the lateral resolution for the SAFT of approximately 1.5 and 1.6% at the depth of 12 and 32 mm, respectively. Concurrently, however, the visualization depth increase for the RMA is shown in comparison with the SAFT. Specifically, the scattered echo amplitude increase by the factor of 1.36 and 1.12 at the depth of 22 and 32 mm is demonstrated. It is also shown that the RMA runs about 30% faster than the SAFT and about 12% faster than the DA method