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The total focusing method (TFM) is often considered to be the ‘gold standard’ for ultrasonic imaging in the field of nondestructive testing. The use of matrix phased arrays as probes allows for high-resolution volumetric TFM imaging. Conventional TFM imaging involves the use of full matrix capture (FMC) for ultrasonic signals acquisition, but in the case of a matrix phased array, this approach is associated with a huge volume of data to be acquired and processed. This severely limits the frame rate of volumetric imaging with 2D probes and necessitates the use of high-end equipment. Thus, the aim of this research was to develop a novel design method for determining the optimal sparse 2D probe configuration for specific conditions of ultrasonic imaging. The developed approach is based on simulated annealing and involves implementing the solution of the sparse matrix phased array layout optimization problem. In order to implement simulated annealing for the aforementioned task, its parameters were set, the acceptance function was introduced, and the approaches were proposed to compute beam directivity diagrams of sparse matrix phased arrays in TFM imaging. Experimental studies have shown that the proposed approach provides high-quality volumetric imaging with a decrease in data volume of up to 84% compared to that obtained using the FMC data acquisition method.

The use of sparse matrix phased arrays can increase the speed of 3D-imaging of the internal structure of objects in ultrasonic nondestructive testing using the Total Focusing Method. The sparse transducer configuration determines the quality of the results. An application of Simulated Annealing for determining the configurations of sparse matrix phased arrays is discussed in terms of the restoration of high quality images of the internal structure of test objects. The performance of the configuration obtained by Simulated Annealing is verified by computer modeling.

Quality of the components in the mechanical engineering is of the utmost importance. Most of quality control procedures can be provided by advanced quality assurance methods that enable visualization of inner structure of a component within all of the occurring defects. This paper suggests an innovative post-processing technique for Full-Matrix ultrasonic imaging with Matrix phased arrays in the case of immersion testing. Evaluation of the reliability was performed by simulation via CIVA software as well as by experimental testing of a real component with given defects. The obtained results of the research demonstrated high sensitivity and accuracy of the suggested technique.

This paper introduces the subarray partition based on the sparse array weighted K‐means clustering method, which extends the conventional K‐means clustering method through the inclusion of a weight matrix approach. This matrix is derived by recording the frequency of each element's occurrence across multiple independent sparse arrays, thereby generating a frequency matrix. The performance of SWKCM is demonstrated through simulations and comparisons with four similar methods. To assess the effectiveness and superiority of the SWKCM, it is applied to the subarray partition of a 40×40 uniform planar phased array and compared with the other four methods. The simulation results show that the proposed SWKCM method maintains comparable sidelobe suppression capabilities to those of KCM, achieving a normalized peak sidelobe level of ‐43.1076 dB. Furthermore, compared to the K‐means clustering method, the sparse array weighted K‐means clustering method significantly enhances the stability of subarray partition outcomes, as evidenced by a reduction in the peak sidelobe level standard deviation from 1.0991 to 0.8104, resulting in a 26.3% decrease in variability.

This paper proposes a cooperated range ambiguous clutter suppression method for moving target detection in the background of range-ambiguous clutter with a phased array (PA)–frequency diverse array (FDA) dual-mode radar. With the FDA mode, the range-ambiguous clutters are discriminated in the transmit spatial frequency domain, and thus the clutter covariance matrixes (CCMs) corresponding to unambiguous and ambiguous regions can be independently estimated. Therefore, the enhanced CCM can be reconstructed by using a linear combination of these distinguished CCMs from different range regions. With the PA mode, the enhanced CCM is applied, thus taking advantages of its high beampattern gain as well as alleviating the range ambiguous clutter suppression problem. Simulation results are presented to verify the effectiveness of the proposed method in range-ambiguous clutter scenarios.

In comparison to phased array (PA) radar that just transmits a beampattern with angle-dependent, frequency diverse array (FDA) radar with adding a feature of distance dimension performs well in main-beam deceptive jamming suppression domain. However, in practical conditions, estimating an inaccuracy of the covariance matrix(CM) has a significant negative impact on algorithm performance, also as a mismatch of target SV has. Hence, a robust adaptive beamforming technique comes up in this article that selects the principal eigenvector to get accurate signal steering vectors (SV), further gets the reconstruction interference-plus-noise CM (IPNCM). According to experiments, the proposed algorithm keeps a robust and good performance under non-ideal circumstances.

In this work, one-dimensional (1D) and 2D scan phased array antennas for 60 GHz radio communication and radar sensing systems are proposed, studied and experimentally validated in the substrate-integrated waveguide technology. A linearly polarised phased array with 1D scanned beams in the first part of this study and a right-hand circularly polarised (CP) array with 2D scanned beams in the second part are presented and discussed in detail. In the demonstrated 1D phased array, dielectric rod antenna is used as radiating elements to form 1 × 4 linear array and then a planar Butler matrix is integrated along with the array to obtain phase-steered beams. In the 2D phased array, CP radiating elements are used to form 2 × 4 array and then a folded Butler matrix is used to feed the CP array. Simulated and measured characteristics of these two phased array antenna radiation parameters are compared. The proposed phased arrays can be integrated into 60 GHz and other millimetre-wave radar and radio systems as an integrated antenna front-end.

Millimeter wave (mm-Wave) technology is likely the key enabler of 5G and early 6G wireless systems. The high throughput, high capacity, and low latency that can be achieved, when mm-Waves are utilized, makes them the most promising backhaul as well as fronthaul solutions for the communication between small cells and base stations or between base stations and the gateway. Depending on the channel properties different communication systems (e.g., beamforming and MIMO) can accordingly offer the best solution. In this work, our goal is to design millimeter wave beamformers for switched beam phased arrays as hybrid beamforming stages. Specifically, three different analog beamforming techniques for the frequency range of 27–33 GHz are presented. First, a novel compact multilayer Blass matrix is proposed. Second, a modified dummy-ports free, highly efficient Rotman lens is introduced. Finally, a three-layer true-time-delay tree topology inspired by microwave photonics is presented.

The hybrid phased multiple‐input‐multiple‐output (MIMO) radar with subarray partition can provide the transmit coherent gain of phased array and the waveform diversity of MIMO radar. The current researches mainly focus on the different subarray partition schemes of the transmit array. In this letter, a full phased‐MIMO (FPMIMO) radar with equally overlapped subarrays is introduced, and a robust adaptive transmit/receive beamforming algorithm is proposed based on the virtual interference‐plus‐noise covariance matrix (INCM) reconstruction and the virtual steering vector estimation. In the FPMIMO radar, the conventional beamforming is used for the signal transmission and reception on each subarray, and all subarrays can be assumed as a uniform linear array. Based on the presumed uniform linear array, the virtual INCM can be reconstructed by Eigen‐decomposition of the reconstructed INCM, and the virtual steering vector can be obtained by the estimated steering vector. With fewer antenna elements and sampling channels in the FPMIMO radar, simulation results demonstrate better performance of the proposed algorithm in a wide range of input signal‐to‐noise ratio.

With the wide application of additive manufacturing components and composite materials, it is of great significance to detect defects with non-destructive testing methods in the material manufacturing process and in service. Due to the strong attenuation and inhomogeneity characteristics, it is inefficient and poor imaging results to detect its internal defects by conventional ultrasonic testing methods. To improve the detection accuracy, this paper proposes an improved imaging algorithm with time reversal-total focusing method (TR-TFM) imaging technology to improve the defects detection in strongly attenuating materials. The experimental results show that the amplitude of the defect signal is increased by 8.30 dB, and compared with total focusing method (TFM), the diameter of the detected defect with TR-TFM imaging is increased from 1.20 mm to 1.60 mm, which is more adjacent to the accurate size. Meanwhile, with the sparse matrix based on FMC data, TR-TFM could obtain the same image quality with the approximate time of TFM imaging.