Method For Arrays Research Articles

Error Compensation Method for Pedestrian Navigation System Based on Low-Cost Inertial Sensor Array.

In the pedestrian navigation system, researchers have reduced measurement errors and improved system navigation performance by fusing measurements from multiple low-cost inertial measurement unit (IMU) arrays. Unfortunately, the current data fusion methods for inertial sensor arrays ignore the system error compensation of individual IMUs and the correction of position information in the zero-velocity interval. Therefore, these methods cannot effectively reduce errors and improve accuracy. An error compensation method for pedestrian navigation systems based on a low-cost array of IMUs is proposed in this paper. The calibration method for multiple location-free IMUs is improved by using a sliding variance detector to segment the angular velocity magnitude into stationary and motion intervals, and each IMU is calibrated independently. Compensation is then applied to the velocity residuals in the zero-velocity interval after zero-velocity update (ZUPT). The experimental results show a significant improvement in the average noise performance of the calibrated IMU array, with a 3.01-fold increase in static noise performance. In the closed-loop walking experiment, the average horizontal position error of a single calibrated IMU is reduced by 27.52% compared to the uncalibrated IMU, while the calibrated IMU array shows a 2.98-fold reduction in average horizontal position error compared to a single calibrated IMU. After compensating for residual velocity, the average horizontal position error of a single IMU is reduced by 0.73 m, while that of the IMU array is reduced by 64.52%.

Interface stress analysis and bonding strengthening exploration of metal layer on the laser-activated copper-clad AlN

Aluminum nitride ceramics has excellent thermal conductivity and insulation property, making it a kind of excellent electronic packaging material. But enhancing the bonding strength between the metal layer and aluminum nitride (AlN) ceramic is a challenging problem. Especially regarding the lack of accurate data analysis on the stress between interfaces, enhancing adhesive strength still relies on blind attempts. By using the finite element method, this study reveals that the shear stress generated between the metal/ceramic interface is concentrated at the interface edge. Based on this finding, a method of inserting micro-pore arrays at the edge is proposed to enhance the interfacial bonding strength. The simulation results show that by inserting micro-pores with an appropriate density, the interface shear stress between metal and ceramic can be reduced obviously by 36 %. Finally, vertical peel-off verification experiments were designed. After inserting micro-pores to the interface, the bonding strength of the interface increased from 8.75 MPa to 11.69 MPa, and the performance was improved by 33.6 %. The experimental results were consist with the simulation results and indicated that the micro-pores had a significant effect on improving the bonding strength.

Topology Optimization Design Method for Acoustic Imaging Array of Power Equipment.

Acoustic imaging technology has the advantages of non-contact and intuitive positioning. It is suitable for the rapid positioning of defects such as the mechanical loosening, discharge, and DC bias of power equipment. However, the existing research lacks the optimization design of microphone array topology. The acoustic frequency domain characteristics of typical power equipment are elaborately sorted out. After that, the cut-off frequencies of acoustic imaging instruments are determined, to meet the needs of the full bandwidth test requirements. Through a simulation calculation, the circular array is demonstrated to be the optimal shape. And the design parameters affect the imaging performance of the array to varying degrees, indicating that it is difficult to obtain the optimal array topology by an exhaustive method. Aimed at the complex working conditions of power equipment, a topology optimization design method of an acoustic imaging array for power equipment is proposed, and the global optimal solution of microphone array topology is obtained. Compared with the original array, the imaging performance of the improved LF and HF array is promoted by 54% and 49%, respectively. Combined with the simulation analysis and laboratory test, it is verified that the improved array can not only accurately locate the single sound source but also accurately identify the main sound source from the interference of the contiguous sound source.

Energy efficient FPGA implementation of an epileptic seizure detection system using a QDA classifier

Epilepsy is a severe neurological disorder that causes seizures. It is detected by analyzing the electrical impulses of the human brain. Monitoring the brain is commonly done using an electroencephalogram (EEG). Seizure detection from the large recorded EEG dataset is a demanding task. However, numerous machine learning classifiers and the appropriate features can detect seizures. The Hjorth and statistical parameters are used in this study to provide an effective method for field programmable gate array (FPGA) realization of epileptic seizure detectors from EEG signals. Mobility, interquartile range (IQR), median absolute deviation (MAD), energy, non-linear energy, and simple square integral (SSI) are the various features analyzed in this work. The hardware architecture of the seizure detection system is captured in Verilog hardware descriptive language and realized on the Artix-7 FPGA. This paper presents three separate seizure detection models designed by pairing three different features with the Quadratic discriminant analysis (QDA) classifier. Among these three models, the energy and non-linear energy-based seizure detection system offers better performance than existing seizure detection systems because it possesses the lowest dynamic power consumption (0.116 µW), the highest design accuracy (99.4 %), and the highest sensitivity (100 %), which makes it the best seizure detection system for real-time applications.

Digital light processing-based bioprinting of microtissue hydrogel arrays using dextran-induced aqueous emulsion ink

As a microscale three-dimensional bionic model, a microtissue array is a promising method for disease modeling and drug screening. Digital light processing (DLP) 3D bio-printing technology with the capabilities of excellent printing speed and resolution shows great potential for fabricating microtissue arrays. However, the outcomes of the microtissue arrays using DLP are limited by the shortage of biomaterials. In this work, we prepare hydrogel microtissues by combining DLP printing technology with biphasic bio-ink consisting of gelatin methacrylate (GelMA) and dextran. GelMA/ dextran is mixed to form bio-inks with different volume ratios, which can achieve high-precision printing of various patterns. Due to the presence of dextran, the bio-inks form the internal porous structure of the hydrogel in the printed patterns. The pore size is related to the proportion of dextran in bio-inks, and the pore size of hydrogel becomes smaller with the increase of dextran ratio. In addition, the adipose-derived stem cells (ADSCs) cells encapsulated in the porous hydrogels can maintain a high survival rate of 98.01% after 3 days of culture, and the larger pore size in the hydrogels promotes cell migration. Combining the DLP printing system with the porous hydrogel allows multiple micro-size geometric pattern hydrogels to be printed simultaneously to form microtissue arrays. In this study, a new bio-ink suitable for microtissue arrays is proposed, and a simple, accurate, and high-throughput biological manufacturing method for microtissue arrays is developed, thus providing a valuable tool for drug screening and tissue engineering.

Fault Diagnosis Method for Photovoltaic Arrays Based on Support Vector Machines

A fault diagnosis method for photovoltaic arrays based on Support Vector Machines (SVM) is proposed to address four typical faults of photovoltaic arrays (short-circuit, open-circuit, aging, shadowing). MATLAB is used to simulate the faults in the photovoltaic array, obtaining four characteristic parameters under different faults: short-circuit current (Isc), open-circuit voltage (Uoc), current at the maximum power point (Im), and voltage at the maximum power point (Um). These parameters are used as training samples to establish a classification model through the SVM algorithm for training and verification. Simulation results show that this method can accurately diagnose the typical faults of the photovoltaic array, and the fault diagnosis accuracy is high.

Method of characteristic modes

In recent years, the number of works on the method of characteristic modes and problems solved with its help has increased significantly, which indicates an awareness of its potential and, in connection with this, a growing interest in this approach. The attractiveness of this method lies in the fact that it provides a clear physical picture of the occurring phenomena and the ensuing opportunity to build on this basis methods for creating structures with the required parameters and combating undesirable phenomena. Unfortunately, in the Russian-speaking segment of applied electrodynamics, very few researchers are engaged in the development and application of the approach under consideration. The purpose of this work is to increase the interest of Russian-speaking researchers in the method of characteristic modes. A review of publications devoted to the method of characteristic modes, both early, fundamental and already classic, associated with the names of R.J. Garbacz and R.F. Harrington, and those which have appeared in recent years and offer generalizations of the method for various electrodynamic structures, has been carried out. This includes composite structures consisting of a set of metal and dielectric bodies of various configurations. In addition, variants of the method for antenna arrays of both infinite periodic and finite sizes have been considered. Issues related to modal tracking problems, orthogonal properties of characteristic modes and improving the convergence of solutions have been considered. Much attention is paid to works containing solutions to specific practical electrodynamic problems using the method of characteristic modes. The works have been shown, in which simple and effective approaches based on the method of characteristic modes are given for the design of a ship's HF antenna system, on-board aircraft antennas in the short-wave region, antennas placed on the platform of a battle tank, and the concept of designing an antenna for an electrically small-unmanned aerial vehicle has been presented. Options for solving the problem of reducing the mutual coupling of elements in antenna arrays have been shown. Attention is paid to MIMO antennas, antennas for smartphones, systems with specified radiation zeros, antennas using metasurfaces. According to the authors, the characteristic mode method, taking into account the increasing possibilities of its application, will make it possible to take the next step in the development, analysis or synthesis of new antenna structures that meet ever-increasing modern requirements.

Fast deconvolved beamforming For arbitrary arrays based on beam-domain sparse Bayesian learning

Aiming at the problem that the conventional deconvolved beamforming methods cannot be directly applied to the specific array with a shift-variant point spread function and also have considerable computational workload, a deconvolved beamforming method for arbitrary arrays based on beam-domain sparse Bayesian learning(SBL) is proposed. First, generalized convolution model for arbitrary arrays in beam-domain is derived. Conventional beamforming is used to obtain several complex output beams. Then, to improve the accuracy of direction of arrival(DOA) estimation, the off-grid SBL method which adopts a coarse grid and takes the sampled positions in the coarse grid as the adjustable parameters is applied to achieve deconvolution of complex output beams. Controlling the number of output beams from the conventional beamforming can accelerate the off-grid SBL method while maintaining reasonable accuracy. The simulation results show that the proposed method provides enhanced recovery performance and higher DOA estimation accuracy comparable to the traditional SBL beamforming method in element domain at the same grid interval. Especially for short and dense arrays, it can achieve a decrease in computational complexity by one to two orders of magnitude with the same accuracy.

GHOST target suppression for distributed multi-array localization using temporal and spatial correlations

We propose a ghost target suppression method for distributed multi-array localization. Triangulation, included in bearings-only target localization method for the well-separated array, is highly dependent on bearing measurements. Its performance is degraded by ghost targets from the ambiguity of bearing measurements. The proposed method is based on the assumption that received signals from the same target have similar frequency components within short-term time and at different locations. We utilize the consistency of acoustic signals in Frequency-Azimuth plots by measuring the frequency component similarities of the target signal over time at a single array (temporal information) and across different arrays (spatial information). The ghost target suppression is evaluated using in situ data from Swellex-96 S5 Event and results reveal the target track along time with much less ghost targets. [Work supported by Korea Research Institute for defense Technology planning and advancement(KRIT)—Grant funded by the Korea government(DAPA(Defense Acquisition Program Administration))(No. KRIT-CT-23-026, Integrated Underwater Surveillance Research Center for Adapting Future Technologies, 2024).]

A multivariate reconfiguration method for rooftop PV array based on improved northern goshawk optimization algorithm

Photovoltaic (PV) power has become a crucial solution to the escalating energy crisis. Among the various implementations, Rooftop PV power generation systems (RPVPGS) are predominant in PV buildings. However, RPVPGS will face challenges such as reduced output power due to array fault or shading, leading to fluctuations in Building-Integrated PV (BIPV) power generation. This paper attempts to solve this problem by proposing a novel multivariate reconfiguration method based on the improved northern goshawk optimization algorithm (INGO). The aim is to find the optimal state of RPVPGS under various conditions. In this paper, extensive simulations were conducted on the experimental platform to assess the feasibility and effectiveness of the proposed method. It is worth noting that INGO outperforms existing technologies such as Arrow SoDuku and Zig-zag for the evaluation metrics mentioned in the article. Furthermore, rigorous simulation experiments were conducted on the semi-physical platform to validate the proposed approach. The power enhancement percentage deviation was between +0.1% to +0.2%. These results unequivocally demonstrate that the INGO-based multivariate reconfiguration method accurately reconfigures RPVPGS, ensuring the efficiency and stability of BIPV systems.

Mask-Moving-Lithography-Based High-Precision Surface Fabrication Method for Microlens Arrays.

Microlens arrays, as typical micro-optical elements, effectively enhance the integration and performance of optical systems. The surface shape errors and surface roughness of microlens arrays are the main indicators of their optical characteristics and determine their optical performance. In this study, a mask-moving-projection-lithography-based high-precision surface fabrication method for microlens arrays is proposed, which effectively reduces the surface shape errors and surface roughness of microlens arrays. The pre-exposure technology is used to reduce the development threshold of the photoresist, thus eliminating the impact of the exposure threshold on the surface shape of the microlens. After development, the inverted air bath reflux method is used to bring the microlens array surface to a molten state, effectively eliminating surface protrusions. Experimental results show that the microlens arrays fabricated using this method had a root mean square error of less than 2.8%, and their surface roughness could reach the nanometer level, which effectively improves the fabrication precision for microlens arrays.

Efficient method for modeling large-scale arrays of optical nanoresonators based on the coupling theory of quasinormal mode.

We propose an efficient method for calculating the electromagnetic field of a large-scale array of optical nanoresonators based on the coupling theory of quasinormal mode (QNM). In this method, two approaches of the scattered-field reconstruction and stationary-phase-principle calculated plane-wave expansion are developed to obtain the regularized QNM (RQNM) in different regions. This accurate and efficient calculation of RQNM resolves the far-field divergence issue of QNMs in the QNM-coupling theory, thus enabling a rapid computation of the electromagnetic field of a large-scale array of optical nanoresonators, which is a challenging task for full-wave numerical methods. Using this method, we consider the numerical example of the radiation problem of a single point source in a large-scale periodic array of optical nanoantennas. In comparison to full-wave numerical methods, this method significantly reduces the computation time by 1∼2 orders of magnitude while maintaining accuracy. The high computational efficiency and physical intuitiveness of the method enables to clarify the impact of array size (exceeding 50 × 50 wavelengths), period and field-coupling range (far beyond the tight-binding approximation) on the optical response. The proposed method and results can provide an efficient tool and guidance for the design of large-scale arrays of optical nanoresonators.

Theoretical and numerical simulation to control the wideband three-dimensional interfering noise by the broadband constant beam pattern method for a spherical array

The broadband constant beam pattern (CBP) spherical array synthesis theory is applied to suppress or to cancel wideband three-dimensional interfering noise sources by implanting zeros in the array's original synthesized shading function. This modified array angular shading function can be expanded by a series of spherical harmonics that will converge to the beam pattern in the far-field such that the created nulls are in the wideband interfering noise source directions per the CBP theory where the ratio of the spherical array radius to the operating frequency wavelength is large. The simulated numerical examples given for this wideband noise source suppression method demonstrate that a broadband CBP performance is maintained for the spherical array with a Legendre polynomial shading function, the classic Dolph–Chebyshev shading function, or a combination. With the CBP design, one set of the real shading functions works for all frequencies in the array's operating band to cancel or to suppress three-dimensional wideband interfering noise sources.

Parallel Calibration Method for Phased Array Based on Multiple-Period Time Modulation

Parallel Calibration Method for Phased Array Based on Multiple-Period Time Modulation

A Frequency–Azimuth Spectrum Estimation Method for Uniform Linear Array Based on Deconvolution

The frequency–azimuth (FRAZ) spectrum is a critical characteristic in passive target detection and tracking, as it encapsulates information regarding the signal’s frequency and azimuth. However, due to the inherent limitations in the sonar array’s physical aperture and the analysis time of the system, the signal often suffers from undersampling in both spatial and temporal dimensions. This undersampling leads to energy leakage across the azimuth and frequency domains, adversely affecting the resolution of the FRAZ spectrum. Such a reduction in resolution hampers multitarget resolution and feature extraction. To address these challenges, this study introduces a deconvolution-based FRAZ spectrum estimation method tailored for uniform linear arrays. The proposed method initiates by decoupling the azimuth and frequency in the FRAZ spectrum, forming a two-dimensional point scattering function that possesses shift-invariance. Subsequent to this, the power spectrum and the two-dimensional point scattering function undergo deconvolution using the Richardson–Lucy (R–L) iterative algorithm. The final stage involves calculating the signal azimuths and frequencies based on the deconvolution results from the preceding step. Comparative analyses involving simulations and sea test results reveal that the proposed method achieves a narrower main lobe width and diminished background noise in contrast to traditional FRAZ spectrum estimation techniques. This improvement is instrumental in minimizing the target’s energy leakage in both the azimuth and frequency domains.

An Acoustic Array Sensor Signal Recognition Algorithm for Low-Altitude Targets Using Multiple Five-Element Acoustic Positioning Systems with VMD

To solve the problem in target acoustic signal processing and recognition when the target flies at a low altitude based on the acoustic positioning system, which is often affected by external interference and brings false information, this paper proposes a target signal processing and recognition algorithm for low-altitude target acoustic positioning based on variational modal decomposition and the test method of multiple five-element acoustic arrays. This algorithm uses VMD to decompose the target signal into modal components with different central frequencies and then performs wavelet threshold processing on the low-frequency part of the signal. After determining the remaining signal components and the low-frequency part’s threshold, the residual component is reconstructed. Based on the test principle and calculation model of the five-element acoustic positioning system, following processing of the low-altitude target acoustic positioning signal using variational modal decomposition, the cross-correlation function method is introduced to perform correlation operations on the basic array of five acoustic sensors and then obtain the time value and time difference of the target acoustic information in each acoustic sensor, ultimately determining the spatial position of the target. Finally, we used the data fusion processing method for target coordinates in multi-acoustic basic arrays to determine the actual target position. By comparing the results obtained using the high-speed camera method with those of the proposed approach, it was found that the average error in the test area of 100 × 100 m was less than 1 m.

Low-Complexity DOA Estimation Method Based on Joined Coprime Array

In this article, the elimination of ambiguity of a joined coprime array has been examined, with a focus on such of its properties as large aperture size and complete degree of freedom (DOF). The existing methods suffer from a high degree of computation complexity due to the loss constant characteristic and high peak searching. Therefore, in this paper, a DOA estimation method for a jointed coprime array, characterized by a low degree of computational complexity, is proposed. The variance of the diagonal eigenvalues of the estimated covariance matrix is designed to enhance the accuracy of the covariance matrix of the joined coprime array. Then, the Capon beamforming methods is employed for peak searching. The simulation shows that the proposed method accomplishes accurate estimation with shorter computation times and fewer operations compared to other DOA estimation methods.

An optimization power method for Photovoltaic array by tracking Maximum Average Current through Diode of Boost Converter

In this paper, a method to optimize the power delivered by the Photovoltaic array (PV array) is presented by tracking the Maximum Average Current (MAC) passing through the diode of DC/DC boost converter. The main difference between the proposed method and the other Maximum Power Point Tracking (MPPT) methods is that instead of tracking maximum power point directly on PV array, this method enables to search the maximum power of PV array by tracking the maximum power output of the DC/DC converter with only one current sensor. An hybrid power system, which includes a PV array, a DC/DC boost converter, an ideal battery and a resistor, is built and simulated in MATLAB/Simulink. The comparison between analytical and simulated results has proven that this method could be applied under various irradiation and photovoltaic temperature conditions.

Evolutionary Algorithm-Inspired Binary Sequence-Based Hybrid Fault Detection Method for Nonuniformly Excited Linear Antenna Array

In this article, a novel method of fault detection in nonuniformly excited linear antenna array has been reported. This method uses an evolutionary algorithm-based technique to generate approximate radiation pattern in tune with reference faulty pattern for a nonuniformly excited linear antenna array. Based on the approximation, a binary sequence-based method of exact fault detection has been developed. In order to illustrate the effectiveness of the method, 12- and 20-element Dolph Tschebyscheff linear antenna array with amplitude fault has been considered. Superiority of the proposed method has been demonstrated through comparative study.

Passive Acoustic Mapping for Convex Arrays With the Helical Wave Spectrum Method.

Passive acoustic mapping (PAM) has emerged as a valuable imaging modality for monitoring the cavitation activity in focused ultrasound therapies. When it comes to imaging in the human abdomen, convex arrays are preferred due to their large acoustic window. However, existing PAM methods for convex arrays rely on the computationally expensive delay-and-sum (DAS) operation limiting the image reconstruction speed when the field-of-view (FOV) is large. In this work, we propose an efficient and frequency-selective PAM method for convex arrays. This method is based on projecting the helical wave spectrum (HWS) between cylindrical surfaces in the imaging field. Both the in silico and in vitro experiments showed that the HWS method has comparable image quality and similar acoustic cavitation source localization accuracy as the DAS-based methods. Compared to the frequency-domain and time-domain DAS methods, the time-complexity of the HWS method is reduced by one order and two orders of magnitude, respectively. A parallel implementation of the HWS method realized millisecond-level image reconstruction speed. We also show that the HWS method is inherently capable of mapping microbubble (MB) cavitation activity of different status, i.e., no cavitation, stable cavitation, or inertial cavitation. After compensating for the lens effects of the convex array, we further combined PAM formed by the HWS method and B-mode imaging as a real-time dual-mode imaging approach to map the anatomical location where MBs cavitate in a liver phantom experiment. This method may find use in applications where convex arrays are required for cavitation activity monitoring in real time.