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To solve the problem of aperture fill time (AFT) for wideband sparse arrays, variable fractional delay (VFD) FIR filters are applied to eliminate linear coupling between spatial and time domains. However, the large dimensions of the filter coefficient matrix result in high system complexity. To alleviate the computational burden of solving VFD filter coefficients, a novel multi–regultion minimax (MRMM) model utilizing the sparse representation technique has been presented. The error function is constrained by the introduction of L2–norm and L1–norm regularizations within the minimax criterion. The L2–norm effectively resolves the problems of overfitting and non–unique solutions that arise in the sparse optimization of traditional minimax (MM) models. Meanwhile, the use of multiple L1–norms enables the optimal design of the smallest sub–filter number and order of the VFD filter. To solve the established nonconvex model, an improved sequential–alternating direction method of multipliers (S–ADMM) algorithm for filter coefficients is proposed, which utilizes sequential alternation to iteratively update multiple soft–thresholding problems. The experimental results show that the optimized VFD filter reduces system complexity significantly and corrects AFT effectively in a wideband sparse array.

Power transformers play a critical role in power systems, and the early detection of their faults and defects, accounting for over 30%, can be achieved through abnormal sound analysis. Sound source localization based on microphone arrays has proven effective in focusing on the troubleshooting scope, preventing potential severe hazards caused by delays in fault removal, and significantly reducing operational and maintenance difficulties and costs. However, existing microphone array-based sound source localization algorithms face challenges in maintaining both accuracy and simplicity and especially suffer from a sharp decrease in performance when dealing with multiple sound sources. This paper presents a multi-sound source localization algorithm for transformer faults based on polyphase filters, integrating the sum-difference monopulse angle measurement technique into the microphone array. Firstly, the signals received from the transformers are divided into multiple subbands using polyphase filters, allowing for multi-source separation and reducing the sampling rate of each subband. Next, the time-domain signals in subbands subject to noise suppression are processed into sum and difference beams. The resulting beam outputs are transformed into frequency-domain signals using the Fast Fourier Transform (FFT), effectively enhancing the signal-to-noise ratio (SNR) for separate sound sources. Finally, each subband undergoes sum-difference monopulse angle measurement in the frequency domain to achieve the high-precision localization of specific faults. The proposed algorithm has been demonstrated to be effective in achieving higher localization accuracy and reducing computational complexity in the presence of actual amplitude-phase errors in microphone arrays. These advantages can facilitate its practical applications. By enabling early targeting of fault sources when abnormalities occur, this algorithm provides valuable assistance to operation and maintenance personnel, thereby enhancing the maintenance efficiency of transformers.

This study develops a novel design scheme based on engineering fluid mechanics for the single-pipe-type sludge drainage mechanism of sedimentation tanks in the wastewater treatment industry. A laboratory-scale clarifier is fabricated for experimental verification. Sludge drainage ratio and suspended solids (SS) of inflow are selected as two factors for laboratory experiments, and SS values are measured to evaluate the performance of the sludge drainage pipe. Experiment data show that the designed single sludge drainage pipe can successfully achieve the supposed task with a coefficient of variation (CV) of SS less than 8.5%. The variation scope of CV from 1.5% to 8.3% suggests that the sludge drainage performance is relatively steady. Nine sets of 3D computational fluid dynamic (CFD) simulations, which is based on the inhomogeneous Eulerian–Eulerian multiphase model, were conducted for a comprehensive exploration and assessment. Results reveal noticeable deviations of the characteristics of the fluid in the outermost orifice of the sludge drainage pipe from the designed value. Although the fluid velocity through each orifice is matched with the designed values, the mass flowrate differs with a maximum of four times the designed value and a standard deviation of 0.4 of hole among the nine simulations. This study also suggests some considerations in the design process and routine operation of the single-pipe-type sludge drainage system.

This paper proposes a modified fast off‐grid L1‐SVD (M‐FOGL1SVD) method for direction of arrival (DOA) estimation. Unlike FOGL1SVD, after obtaining the positions of the nonzero rows of the signal sources, the off‐grid overcomplete basis matrix is used to update the signal sources, thus improving the estimation accuracy of it. In addition, to reduce the approximate error of the first‐order off‐grid model, a second‐order off‐grid model is introduced through a further Taylor expansion of the steering vector. Finally, the formula for solving the off‐grid gap under the novel model is derived. Extensive simulation results indicate that the proposed algorithm has better performance than FOGL1SVD in terms of DOA estimation precision.

The transition from up-flow anaerobic sludge blanket (UASB) reactors to expanded granular sludge bed (EGSB) reactors presents challenges for traditional symmetric critical gas–liquid–solid (GLS) separators, including high spatial occupation, fluid-energy consumption, and reduced separation efficiency. This study introduced a novel GLS separation mechanism based on vortex circulation-induced deposition, agglomeration, and flowback of solid separation. Leveraging this mechanism, an innovative asymmetrical laboratory-scale GLS separator was developed and tested with both granular and flocculent sludge. The new prototype demonstrates superior solid separation performance, achieving 98.3% for granular sludge and 96.0% for flocculent sludge. It features a simple structure and optimized flow paths, resulting in approximately 30% reduction in height and 14.8% less material consumption compared to existing models. Flocculent sludge shows greater sensitivity to operational factors than granular sludge, with higher sludge concentration and smaller fragment size being preferable for high separation efficiency. This mechanism is validated by experimental observations and computational fluid dynamics (CFD) simulations, providing a new perspective on GLS separation and establishing the new model as a promising candidate for UASB/EGSB bio-reactors.

The phase-only transmit nulling method is widely used in narrowband arrays, but there are few reports of its application in wideband arrays. This paper describes the implementation of adaptive transmit nulls in wideband arrays based on subband phase-only pattern synthesis behind each array element. The filter bank behind each array element partitions the transmit signal into independent subbands and utilizes a phase shifter group in each subband to form frequency invariant spatial nulls in the array’s transmit pattern. The scheme developed in this paper includes an algorithm for computing a wideband phase-only weight vector and a subband phase-only adaptive signal processing method based on band partitioning. The validity of the scheme is proven by theoretical analysis and simulation experiments.

In this study, the effects of non-sidelooking airborne radar clutter dispersion on space-time adaptive processing (STAP) is considered, and an efficient adaptive angle-Doppler compensation (EAADC) approach is proposed to improve the clutter suppression performance. In order to reduce the computational complexity, the reduced-dimension sparse reconstruction (RDSR) technique is introduced into the angle-Doppler spectrum estimation to extract the required parameters for compensating the clutter spectral center misalignment. Simulation results to demonstrate the effectiveness of the proposed algorithm are presented.

In this paper, an efficient direct data domain space-time adaptive processing (STAP) algorithm for moving targets detection is proposed, which is achieved based on the distinct spectrum features of clutter and target signals in the angle-Doppler domain. To reduce the computational complexity, the high-resolution angle-Doppler spectrum is obtained by finding the sparsest coefficients in the angle domain using the reduced-dimension data within each Doppler bin. Moreover, we will then present a knowledge-aided block-size detection algorithm that can discriminate between the moving targets and the clutter based on the extracted spectrum features. The feasibility and effectiveness of the proposed method are validated through both numerical simulations and raw data processing results.

Radar forward‐looking imaging is gaining significance in various applications like battlefield reconnaissance, target surveillance, and precision guidance. Although synthetic aperture radar techniques provide high azimuth resolution but faced limitations in forward‐looking area due to the poor Doppler resolution and the “left‐right” ambiguity problem. Recently, generative adversarial networks have been extensively used for image motion blur removal. This letter proposes an end‐to‐end forward‐looking image enhancing network using generative adversarial network to produce high‐resolution images, improving the efficiency, and quality of imaging. Compared to conventional methods such as the deconvolution‐based methods, this algorithm eliminates the need for design and iterative processes of the observation matrix. Simulated and real radar data validate that this approach offers robust recovery and better performance. This letter propose a generative adversarial network model for radar forward‐looking imaging. The proposed model is based on a dual‐scale discriminator with the feature pyramid network as the central module of the generator. To strengthen the network's backbone, Inception‐ResNet‐v2 is employed. Both simulations and real radar data processing demonstrate a significant improvement in image resolution compared to the real beam imaging method.

Global navigation satellite system (GNSS) reflection signal to form a passive radar system for sea target detection has attracted attention in recent years. Low signal power on the earth’s surface is the main bottleneck of this passive radar system. Prolonging the integration time is an effective way to improve the radar detection ability. However, the range cell migration (RCM) and Doppler frequency migration (DFM) induced by the target motion during the long integration time cause integration gain loss and degrade the detection ability. A long-time hybrid coherent and noncoherent integration method is proposed to overcome such issues. This method uses the keystone transform and the matched filtering function H1 to remove the linear RCM and quadratic RCM, respectively. Then, the long-time integration time is segmented into multiple frames with the same duration. Another matched filtering function H2 is designed to eliminate the DFM. Finally, coherent integration and noncoherent integration operations are implemented inside and among the frames to improve the signal-to-noise ratio of the target-reflected GNSS signal available for detection. A maritime measurement campaign is conducted and confirms the effectiveness of the proposed method for sea target detection. Monte Carlos trials and computational cost analysis show that the detection capability of the proposed method outperforms that of the existing methods, but the computational cost is in the same order as ON3logN.