Ground-penetrating radar (GPR) is a key non-destructive technique for subsurface reconstruction, widely valued for its ability to image buried structures without disruption. Among its various implementations, vehicle-mounted GPR has emerged as particularly suitable for highway tunnel assessment due to its rapid non-contact operation. However, current systems are often constrained by closely spaced antennas that generate strong direct coupling and consequently limit detection depth. To mitigate this issue, this paper proposes an antenna decoupling method based on coherent difference imaging. A differential decoupling model is first established to characterize the relationship between conventional transceiver signals and the derived differential signals, explicitly accounting for parameters such as antenna height and target depth. Furthermore, a coherent difference imaging algorithm is developed, employing a sliding-window coherence process to resolve dual-peak artifacts and restore focused target images. Simulations validate consistent performance across varying antenna heights, while experiments demonstrate over 37.2 dB isolation in the 1–3 GHz band and markedly improved imaging focus compared to conventional configurations, thereby enhancing buried target detection and supporting reliable data interpretation.

A coherent power-load optimization algorithm for wind farm-level yaw control considering wake effects via deep neural network

Helicopter detection plays a vital role in obtaining critical aerial information promptly and ensuring the safety of lives and property. Since a helicopter’s aerodynamic noise primarily consists of main rotor noise, the cyclostationarity of this noise becomes our detection target. This paper proposes a filter based on the Frequency-Shift (FRESH) principle, which is updated using the Adam optimization algorithm. A smoothed global detector is presented to detect the cyclic frequency of rotor noise. The effectiveness of the proposed helicopter detection approach, comprising both the filter and the detector, has been validated through simulations and confirmed by far-field experiments with a ROBINSON R22 helicopter. In these tests, the proposed method was compared against a cyclostationarity adaptive filter based on the Normalized Least Mean Squares (NLMS) algorithm, as well as the traditional Detection of Envelope Modulation on Noise (DEMON) and Cyclic Modulation Coherence (CMC) algorithms. Experimental results demonstrate the superior robustness of the proposed method over these benchmarks. Even at extended ranges between 11 and 13 km, the system retains a consistent detection rate of 77.8%.

ABSTRACT Fault identification is a key objective in oil and gas geophysical exploration, with the coherence cube technique being among the most widely used methods for fault identification. This paper extended the classical C3 coherence algorithm by incorporating structural dip information using the time-shifting properties of FFT. This modification eliminated the need for traditional interpolation methods and effectively addressed the C3 algorithm’s insensitivity to dip at a very low computational cost. To achieve this, we first smoothed and diffused the seismic data using directional derivatives to minimize the impact of noise on dip estimation and coherence calculation. Next, we estimated the dip angle using instantaneous phase. Subsequently, we incorporated the dip information into the coherence algorithm enhanced using complex seismic traces, resulting in a dip-considered coherence method. Application to 2D synthetic data demonstrated that the method effectively eliminates low-value artifacts caused by linear and curved dipping strata, clearly revealing faults. Coherence results from 3D field data also showed significant noise suppression and effective elimination of coherence artifacts and stratigraphic anomalies, highlighted small faults previously obscured by artifacts. Compared to the classical C3 coherence algorithm, the proposed method offered higher resolution, improved noise resistance, and eliminated dip artifacts at a very low computational cost, thereby enhanced discontinuity detection and ensuring accurate fault identification.

For pulse-Doppler radars employing large time-bandwidth product waveforms, coherent integration and detection of weak hypersonic targets are challenged by echo scaling effect and linear range cell migration, which manifests as Doppler cell migration in the two-dimensional frequency domain. Additional compensation is required when targets undergo constant acceleration. To address these issues, this paper proposes an efficient long-time coherent integration algorithm for hypersonic targets with constant velocity, termed NUFFT-EKT. The method, inspired by the Improved Radon Inverse Fourier Transform (IRIFT), exploits the periodicity of raw two-dimensional frequency-domain echoes, while employing the NonUniform Fast Fourier Transform (NUFFT) to implement the Doppler-domain extended Keystone Transform (EKT). A velocity-segmented update strategy is further introduced for the velocity-dependent pulse compression filter construction, significantly reducing update frequency and memory requirements. For accelerating targets, the approach is extended to Dechirp-NUFFT-EKT by applying acceleration search and compensation prior to integration. The proposed algorithm achieves near-optimal performance in terms of output SNR, detection, and parameter estimation, while avoiding the parasitic harmonics along the range dimension inherent in IRIFT, with comparable computational complexity. In scenarios with large Doppler ambiguity numbers, NUFFT-EKT even achieves slightly lower complexity than IRIFT. Numerical simulations confirm the effectiveness and efficiency of the proposed method, demonstrating substantial gains over conventional coherent integration techniques for hypersonic targets.

In recent years, low Earth orbit (LEO) satellite communication has emerged as a focal area of extensive research due to its potential for global broadband connectivity. Multi-carrier direct sequence spread spectrum (MC-DSSS) technology, leveraging the inherent anti-jamming advantages of spread spectrum signals, has shown great promise in enhancing communication reliability. However, the acquisition of MC-DSSS signals in LEO transmission link presents significant challenges, primarily due to the coexistence of extremely low signal-to-noise ratio (SNR) and substantial Doppler effect.To address these issues, this paper proposes an optimal two-dimensional (2D) acquisition framework for MC-DSSS signals. Based on the maximum likelihood (ML) criterion, the proposed framework enables coherent combination of subcarriers with high time resolution, thereby improving the acquisition performance in harsh LEO environments. Furthermore, a two-step low-complexity coherent acquisition algorithm is developed. This algorithm significantly reduces the computational burden while maintaining the performance of fully coherent subcarrier combination, making it more suitable for real-time implementation in resource-constrained LEO communication terminals. Moreover, this paper derives closed-form solutions for the false alarm probability, detection probability, and mean squared error (MSE) in additive white Gaussian noise (AWGN) channel, which are validated through simulations. The results demonstrate that the proposed algorithm achieves 2 dB performance improvement in SNR compared to noncoherent combining method, with a 1024-fold reduction in MSE when the number of subcarriers is 16.

Tunable photoinitiated hydrogel microspheres for quantifying cell-generated forces in complex three-dimensional environments.

Abstract To address the challenge of navigation message demodulation in extremely weak signal environments for satellite navigation receivers during deep space exploration missions, particularly when using a pure Frequency Lock Loop (FLL) tracking mode, this paper proposes a novel differential coherent accumulation message demodulation algorithm. In pure FLL tracking mode, it is difficult to lock the carrier phase, which causes the signal energy to be distributed evenly across the in-phase (I) and quadrature (Q) branches. This significantly degrades the performance of traditional message demodulation methods, which depend exclusively on energy detection in the I branch. This paper uses theoretical analysis to explain how phase ambiguity affects the coherent integration values of the I/Q branches. It also proposes a differential coherent accumulation algorithm to reduce the effect of phase unlocking on message demodulation. Two implementation architectures are innovatively introduced: fixed window length and variable window length. The paper details their specific implementations and compares their performance via simulations. The results indicate that for a bit error rate (BER) of 10-6, the carrier-to-noise ratio (C/N0) thresholds for the variable and fixed window length methods are 24 dB and 27 dB, respectively. This demonstrates a 3 dB sensitivity improvement for the variable window approach. This research provides an effective solution for reliable message demodulation in ultra-weak signal environments for deep space navigation receivers, significantly expanding the applicable boundaries of satellite navigation systems.

Abstract Satellite signal acquisition is a critical component for BeiDou receivers to achieve PNT functionality, with its performance directly determining system availability in complex environments. Traditional time-frequency two-dimensional parallel search methods face two major bottlenecks: computational complexity increases dramatically when processing high-dynamic Doppler shifts, and under weak signal conditions, they struggle to meet high-sensitivity, low-power requirements due to the squaring loss effect and elevated noise floor. To address these challenges, this paper proposes an innovative acquisition architecture. 1) Combining an equivalent frequency compensation cyclic shift search mechanism with sparse Fourier transform (SFT), eliminating traditional two-dimensional traversal, and transforming Doppler search into cyclic shifts to reconstruct frequency search logic. 2) Introducing SFT to efficiently utilize the frequency-domain sparsity of BeiDou signals, computing only significant frequency components to optimize frequency-domain correlation efficiency. 3) Designing an improved differential coherent integration algorithm. For weak signal acquisition, differential coherent technology is applied by constructing a phase difference model between adjacent symbol periods, effectively canceling data bit transition effects and significantly suppressing noise floor elevation, achieving an SNR gain improvement of approximately 3 dB. Compared to conventional methods, under the same hardware conditions, the proposed solution reduces computational complexity by 62 % and improves acquisition sensitivity by 4 dB. For weak signals at -45 dBm, the acquisition success rate reaches 95 %. The novel “Doppler cyclic shift search-SFT” fusion architecture and differential coherent technology provide a new technical approach for efficient, high-sensitivity BeiDou signal acquisition, demonstrating significant theoretical breakthroughs and broad engineering application prospects.

Abstract: With the advancement of digital radio communication systems, there is a growing demand for enhanced spectral efficiency in mobile and hybrid radio systems and networks. To meet these requirements, Multiple-Input Multiple-Output (MIMO) technology is extensively employed in modern radio communication systems. The use of multiple transmitting and receiving antennas in MIMO systems imposes stringent performance requirements on signal processing algorithms. Consequently, the development of fast and efficient signal processing algorithms is a task of significant relevance.The aim of this study is to analyze and optimize space-time coding techniques and signal processing algorithms for MIMO systems. The research focuses on developing an algorithm that ensures the required level of performance while significantly reducing computational complexity. Methods. This study utilizes numerical simulation methods within the MATLAB environment to compare the performance of various signal processing algorithms in MIMO systems over a fading channel.Results. In addressing the research objectives, the principles of constructing space-time code matrices for different coding methods were examined, and coherent signal demodulation techniques were analyzed. Based on this analysis, an algorithm with reduced computational complexity is proposed. A key element of scientific novelty of this work lies in the development and application of a novel approach to approximate the inverse channel matrix, which is a computationally expensive operation, particularly for high-dimensional matrices in coherent demodulation algorithms. This new approach is based on the combined use of the iterative Jacobi method and the Neumann series expansion for the approximation of the matrix inverse.Practical significance. The developed algorithm can be utilized in the design of MIMO systems with a large number of transmitting and receiving antennas, as well as in the application of non-orthogonal coding schemes to increase the coding rate. In such systems, conventional demodulation methods require significant computational resources for inverting the channel matrix, which limits real-world performance. The proposed algorithm mitigates this bottleneck, enabling more practical implementations.

With the extension of signal accumulation time, high-speed and low radar cross section (RCS) aerial vehicles cause serious range cell migration (RCM) and Doppler frequency migration (DFM) in radar echoes, significantly degrading radar detection performance. To address the challenge of weak target detection, long-time coherent integration (LTCI) techniques enhance the signal-to-noise ratio (SNR) by concentrating energy in the time-frequency domain (TFD) or transform domain. However, existing LTCI methods primarily focus on acquiring the target’s initial range parameters during the coherent integration interval (CPI), but neglecting potential distance deviation between the actual range and the initial range after the integration. This paper proposes a novel LTCI algorithm, PSA-FAIR-NUFFT, combining frequency domain angular inverse rotation (FAIR), non-uniform fast Fourier transform (NUFFT), and PID-based search algorithm (PSA). The method effectively integrates signal energy and estimates final range parameters for moving targets. Specifically, FAIR establishes the frequency domain axis rotation relationship to align the target trajectory into the final range unit. Concurrently, NUFFT performs coherent integration as well as the motion parameters estimation. To optimize the rotation angle search efficiency, an objective function based on accumulated peak value is formulated with the PSA improving computational efficiency. This approach achieves precise parameter estimation with low complexity. Furthermore, for multi-target detection scenarios involving mixed-strength targets, a modified CLEAN technique is incorporated to sequentially separate strong and weak targets. Compared with typical LTCI algorithms, both numerical simulation experiments and real data analysis demonstrate the effectiveness and reliability of the proposed algorithm.

The object of this study is the process of receiving multidimensional signals formed on the basis of high-order phase-difference modulation of the data transmission system. The development of mobile networks of the next generations is accompanied by increased requirements for the speed, reliability, and noise immunity of information transmission. Existing modulation methods provide an increase in the speed of information transmission by reducing noise immunity and increasing the spectral width of the signal. The general unsolved problem is the lack of an effective method for forming a multidimensional signal of the nth multiplicity and receiving it based on high-order phase-difference modulation, capable of improving the efficiency of these parameters. The work proposes a method that makes it possible to form a three-dimensional multi-position signal 3D AFM-32, which uses three independent parameters – amplitude, phase, and time. A feature of the result is that noise immunity is ensured without increasing the spectral width of the signal, but due to three-dimensional formatting, which increases the distance between signal points by 50%. A coherent reception algorithm has been developed that provides accurate signal recovery even in the presence of phase or frequency disturbances. It is shown that the reception efficiency is achieved at an averaging interval of not less than M = 20, at which the system demonstrates an error probability at the level of SER≈10⁻8 at Eb/N0 ≈ 17.4 dB. This makes it possible to obtain an energy gain of 2–3 dB compared to QAM-32 and classical AFM. The proposed approach is invariant to phase shifts due to the first and second order phase differences, which eliminates ambiguities during reception. 3D AFM-32 demonstrated higher noise immunity compared to QAM-16/32 and AFM-16/32 under the same conditions. The results could be used in 5G/6G networks, in particular in adaptive OFDM systems, autonomous transport, and telemetry

Rectourethral fistula (RUF) is associated with poor quality of life related to urinary functional symptoms (pneumaturia, fecaluria, urine passing through the rectum) or urinary tract infections (upper or lower, often recurrent). Most are iatrogenic, occurring after surgery such as radical prostatectomy, where their prevalence ranges from 0.03 in various series. RUF can also occur after radiation therapy administered for prostate cancer. Management of RUF is complex and depends on whether the patient has had previous radiation therapy or not. Different surgical techniques have been evaluated, but currently there is no consensus as to the best approach. The York-Mason technique is preferred for simple RUF in patients without prior irradiation, while for more complex cases, with antecedent irradiation, transperineal approaches with muscular flap interposition are often recommended. Evaluation of quality of life is crucial, because management of RUF can have severe consequences on urinary continence and sexual function. Despite successful anatomical repair, patients often continue to suffer from functional sequalae that affect their quality of life. Although progress has been achieved in the treatment of RUF, a coherent and efficient management algorithm is necessary to standardize the practical aspects and improve the outcomes. This update summarizes the different strategies that are available for management of RUF and underscores the importance of an individualized approach.

Abstract Conventional new energy power system microgrid group consistency cooperative control method mainly uses adaptive frequency sag control technique for control frequency coupling, which is easily affected by the dynamic adjustment of the sag coefficient, resulting in high cooperative control cost, therefore, a new new new energy power system microgrid group consistency cooperative control method based on discrete consistency algorithm needs to be designed. That is, the discrete consistency algorithm is used to generate a new energy power system microgrid group consistency cooperative control strategy, and the new energy power system microgrid group consistency cooperative control architecture is designed, so as to realize the power system microgrid group consistency cooperative control. The experimental results show that the real-time power regulation cost, cumulative operation cost and cumulative transmission loss cost of the designed new energy power system microgrid group consistency cooperative control method are lower, which proves that the designed new energy power system microgrid group consistency cooperative control method has a better control effect, lower control loss, and has a certain economic value, and makes a certain contribution to the solution of the current power allocation problem of the microgrid group.

ABSTRACT Runway roughness evaluation plays a vital role in maintaining operational efficiency and guiding maintenance planning for airport ground operations. Conventional measurement methods often suffer from limited spatial coverage, low efficiency, and significant operational disruptions. This study presents an Interferometric Synthetic Aperture Radar (InSAR) approach for runway roughness assessment that achieves wide-area, efficient, and non-intrusive evaluation. The Temporarily Coherent Point InSAR algorithm effectively mitigates specular reflection from runway surfaces, delivering high-precision time-series vertical displacement data. Subsequently, the Nonlinear PCA-Co Kriging method integrates InSAR observations with levelling Digital Elevation Model data, followed by interpolation and resampling to create a high-resolution 3D runway elevation model. From those model, longitudinal profiles of the runway centerline and 6 meters east/west were extracted for Boeing Bump Index (BBI) calculation. Results demonstrate that the Nonlinear PCA-Co Kriging method surpasses traditional Original Kriging and Co-Kriging techniques in detecting elevation changes. The computed Boeing Bump Index shows excellent agreement with vehicle-mounted measurements (minimum correlation coefficient of 0.94, maximum mean absolute error of 0.025 BBI, standard deviation of 0.028 BBI), validating the method's reliability for runway roughness monitoring.

A coherence algorithm is used to detect and classify electrical faults in the stator windings of the induction machine in this paper. The approach can definitely define turn-to-turn and internal shunt faults that occur on the three-phase machine windings. It can also distinguish between the diverse types of the internal shunt faults. The approach requires the acquisition of three-phase voltage measurements at the midpoints and complete terminals of the stator windings of the induction machine. The function of the numerical differential voltage relay can be performed using cross-coherence and auto-coherence coefficients quantified for the voltage measurements to determine and categorize the various faults. A modified configuration for the three-phase stator windings of an induction motor is used to test the technique; in which, each stator winding of the equipment is re-wounded to obtain 20 taps per phase. This configuration aims to construct voltage transformers at the midpoints and complete terminals for the machine stator windings, and to facilitate making comprehensive tests to ensure the effectiveness of the coherence technique. The testing results demonstrate the effectiveness and efficiency of the advanced protection. The experimental findings indicate that the protection’s dependability and security percentages are greater than 98.0%, and the protection’s reliability and accuracy rates are nearly 97.0%. The coherence measure has the ability to discover winding faults, particularly those occurring from turn to turn, differentiate between fault locations, and categorize shunt faults located within the machine protection zone. Additionally, the proposed approach has a high-speed response that is adjustable, and new tripping curves are created.

Tuffaceous fillings are a significant component of the Permian Kuishan sandstone in the North China Platform, and their complex diagenetic processes have a notable impact on the development of clastic rock reservoirs. This study, based on microscopic analysis of reservoirs and combined with quantitative analytical techniques such as electron probe microanalysis, homogenization temperatures of fluid inclusions, micro-area carbon-oxygen isotope analysis, and laser Raman spectroscopy, investigates the influence of tuffaceous interstitial material dissolution on reservoir development in the Permian Kuishan sandstone of the Gaoqing buried hill in the Jiyang Depression, Bohai Bay Basin. The results indicate that the dissolution intensity of tuffaceous interstitial materials can be classified into three levels: strong, moderate, and weak. In the strong dissolution zone, associated fractures and dissolution pores significantly contribute to reservoir porosity, with a positive correlation between dissolution plane porosity and total plane porosity. The reservoir space is characterized by a network of dissolution pores and fractures. The moderate dissolution zone is marked by the development of authigenic quartz, feldspar, and clay minerals, which do not effectively enhance porosity and permeability. The weak dissolution zone contains well-preserved volcanic glass shards, crystal fragments, and clay minerals, representing non-reservoir development sections. Lithology, sedimentary facies, diagenesis, and fractures collectively control the quality of the Permian Kuishan sandstone reservoir in the Gaoqing buried hill of the Jiyang Depression, Bohai Bay Basin. The advantageous zones for reservoir development in this area can be effectively predicted using thickness maps of the Kuishan sandstone, planar distribution maps of sedimentary facies, and fracture prediction maps derived from ant-tracking and coherence algorithms.

3D medical model registration using scale-invariant coherent point drift algorithm for AR

A method is presented to enhance the spatial selectivity of spatial post-filters estimated with first-order directional signals. The approach involves applying non-linear transformations on two different spatial post-filters and combining them with weights found by convex optimization of the resulting directivity patterns. The estimation of the post-filters is carried out similarly to the Cross Pattern Coherence (CroPaC) algorithm. The performance of the proposed method is evaluated in a two- and three-speaker scenario with different reverberation times and angular distances of the interfering speaker. The signal-to-interference, signal-to-distortion, and signal-to-artifact ratios are used for evaluation. The results show that the proposed method can improve the spatial selectivity of the post-filter estimated with first-order beampatterns. Using first-order patterns only, it even achieves better spatial separation than the original CroPaC post-filter estimated using first- and second-order signals.

A computational technique based on a coherence method for fault detection and classification for electrical machine stator windings is presented in this article. The coherence algorithm can identify clearly and concisely inter-turn and shunt faults situated on the 3-phase stator windings of the AC machine. Besides, it can categorize the different types of internal shunt faults. The cross-coherence algorithm performs the functional role of digital differential current to find and classify the internal faults; while, the auto-coherence algorithm acts as an overcurrent detector to define the occurrence of external, internal, or inter-turn faults. A new setup of three-phase induction machine stator windings, where each winding is re-winded to produce 20 taps per phase, is used to examine the approach. The new design is intended to build current transformers at the neutral and supply sides of the three windings, and to simplify conducting comprehensive examinations to verify the efficacy and efficiency of the advanced algorithm. The protection characteristics of the developed algorithm will be analyzed and estimated using the new setup. The test results indicate that the reliability and accuracy of the protection are above 98.7%. The coherence criterion is also useful for monitoring electrical faults, sensing inter-turn faults, distinguishing between external and internal shunt faults, classifying diverse internal shunt faults within the equipment protection zone, and estimating the tripping time when inter-turn faults occur. Furthermore, a new design of protection tripping-characteristic curves is established, and the time response of the computational technique is fast.