Signal Processing最新文献_第5页

Sparse channel estimation and passive beamforming with practical phase shift model for IRS-assisted OFDM systems 基于实际相移模型的irs辅助OFDM系统稀疏信道估计和无源波束形成

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-03-20 DOI: 10.1016/j.sigpro.2025.109997

Shabih Ul Hassan , Zhongfu Ye , Jiancheng An , Md Bipul Hossen

{"title":"Sparse channel estimation and passive beamforming with practical phase shift model for IRS-assisted OFDM systems","authors":"Shabih Ul Hassan , Zhongfu Ye , Jiancheng An , Md Bipul Hossen","doi":"10.1016/j.sigpro.2025.109997","DOIUrl":"10.1016/j.sigpro.2025.109997","url":null,"abstract":"<div><div>Intelligent reflecting surfaces (IRS) enable control of wireless propagation environments and have emerged as a highly promising and cost-effective technology for elevating the performance of future wireless communication systems. Obtaining the passive beamforming gain requires accurate channel state information (CSI), despite the practical challenge posed by its passive reflecting elements, which lack transmitting or receiving capability. Prior research on IRS has mostly used an ideal phase shift model, which assumes that every element reflects the signal fully irrespective of its phase shift. However, achieving this in real-world situations is difficult. This paper proposes a practical phase-shift model that takes into account phase-dependent changes in amplitude within the subgrouping reflection coefficient. This paper presents a new formulation for sparse channel estimation and passive beamforming in IRS subgrouping-assisted orthogonal frequency division multiplexing (OFDM) systems, leveraging a practical phase-shift model. Channel sparsity in the time domain is exploited, taking into account the physical proximity of passive elements and utilizing common sparsity shared among different subgroups using the variational Bayesian inference (VBI) framework. Furthermore, we proposed a stochastic majorization-minimization (SMM) based approach to optimize the IRS phase shifts to maximize the achievable sum-rate for the system, accounting for the practical phase-shift model. The results of the simulation validate the efficiency of the proposed channel estimation and passive beamforming method, showing substantial performance enhancements compared to existing cutting-edge techniques.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"234 ","pages":"Article 109997"},"PeriodicalIF":3.4,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hyperbolic frequency modulated signal analysis using Mellin transform 基于Mellin变换的双曲调频信号分析

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-03-18 DOI: 10.1016/j.sigpro.2025.110007

Liang Zhang , Qinglei Du , Ruihui Peng , Xiangyu Zhang , Hui Chen

引用次数: 0

Periodicity-constrained reweighted generalized minimax-concave regularization and its application in gearbox fault diagnosis 周期约束重加权广义极小极大凹正则化及其在齿轮箱故障诊断中的应用

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-03-17 DOI: 10.1016/j.sigpro.2025.110005

Lichao Yu , Chenglong Wang , Cunfu Wang , Fanghong Zhang , Huageng Luo

{"title":"Periodicity-constrained reweighted generalized minimax-concave regularization and its application in gearbox fault diagnosis","authors":"Lichao Yu , Chenglong Wang , Cunfu Wang , Fanghong Zhang , Huageng Luo","doi":"10.1016/j.sigpro.2025.110005","DOIUrl":"10.1016/j.sigpro.2025.110005","url":null,"abstract":"<div><div>In vibration-based gearbox fault diagnosis, accurately extracting periodic transient signals caused by defects is crucial for achieving fault diagnosis. However, the vibration signals measured in practice are often dominated by interference such as random noise and harmonic signals, making the extraction of the transient component highly challenging. To address the issue, this paper proposes a periodicity-constrained reweighted generalized minimax-concave (PC-ReGMC) regularization, which can effectively filter out interference and accurately reconstruct the periodic transient signals. This method is based on a weighted generalized minimax concave regularization model. First, the weight coefficients are initialized to perform the initial transient signal extraction. Then, the square envelope harmonic product spectrum (SEHPS) is introduced to identify the period of the transient signal, and a periodic weighting strategy based on the sinusoidal function is designed to update the weight coefficients. Finally, by reweighting the generalized minimax concave regularization model, the periodicity constraint is embedded into the optimization process of sparse coefficients, thus imposing penalties on non-periodic components to enhance denoising performance. Through the analysis results of simulations and practical cases, it is demonstrated that the proposed method outperforms other sparse regularization methods and the spectral kurtosis in terms of the reconstruction accuracy of the periodic transient signals, and thus provides more precise gearbox fault diagnosis results.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"234 ","pages":"Article 110005"},"PeriodicalIF":3.4,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Signed graph learning with hidden nodes 带隐藏节点的签名图学习

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-03-17 DOI: 10.1016/j.sigpro.2025.109995

Rong Ye , Xue-Qin Jiang , Hui Feng , Jian Wang , Runhe Qiu

{"title":"Signed graph learning with hidden nodes","authors":"Rong Ye , Xue-Qin Jiang , Hui Feng , Jian Wang , Runhe Qiu","doi":"10.1016/j.sigpro.2025.109995","DOIUrl":"10.1016/j.sigpro.2025.109995","url":null,"abstract":"<div><div>Signed graphs, which are characterized by both positive and negative edge weights, have recently attracted significant attention in the field of graph signal processing (GSP). Existing works on signed graph learning typically assume that all graph nodes are available. However, in some specific applications, only a subset of nodes can be observed while the remaining nodes stay hidden. To address this challenge, we propose a novel method for identifying signed graph that accounts for hidden nodes, termed <em>signed graph learning with hidden nodes under column-sparsity regularization</em> (SGL-HNCS). Our method is based on the assumption that graph signals are smooth over signed graphs, i.e., signal values of two nodes connected by positive (negative) edges are similar (dissimilar). Rooted in this prior assumption, the topology inference of a signed graph is formulated as a constrained optimization problem with column-sparsity regularization, where the goal is to reconstruct the signed graph Laplacian matrix without disregarding the influence of hidden nodes. We solve the constrained optimization problem using a tailored block coordinate descent (BCD) approach. Experimental results using synthetic data and real-world data demonstrate the efficiency of the proposed SGL-HNCS method.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"234 ","pages":"Article 109995"},"PeriodicalIF":3.4,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Joint jamming perception and transmit waveform design for anti-interrupted sampling repeater jamming 抗中断采样中继器干扰的联合干扰感知与发射波形设计

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-03-17 DOI: 10.1016/j.sigpro.2025.109994

Rongqing Wang, Jingyang Xie, Pengjun Huang, Biao Tian

{"title":"Joint jamming perception and transmit waveform design for anti-interrupted sampling repeater jamming","authors":"Rongqing Wang, Jingyang Xie, Pengjun Huang, Biao Tian","doi":"10.1016/j.sigpro.2025.109994","DOIUrl":"10.1016/j.sigpro.2025.109994","url":null,"abstract":"<div><div>Interrupted sampling repeater jamming (ISRJ) is a type of intra-pulse coherent jamming based on digital radio frequency memory (DRFM), which has been widely used in jammers in recent years, posing a serious threat to radar detection. Traditional anti-jamming methods are relatively passive, and the jamming suppression performance depends heavily on the accuracy of parameter estimation. Additionally, most waveform design techniques lack the perception of jammer strategies, resulting in performance degradation when suppressing ISRJ. In order to improve radar anti-jamming performance, a scheme for jointing jamming perception and transmit waveform design is developed in this paper. Firstly, bidirectional double-sliding window pulse edge detection and sliding truncated matched filter (STMF) are employed to extract the ISRJ components in the received echo and estimate the relevant parameters accurately. Subsequently, an intra-pulse dual-parameter agile waveform is designed to increase the difference between the target signal and ISRJ. Furthermore, by extracting the interfered sub-pulse segments, filters based on the fractional Fourier transform (FrFT) are constructed to eliminate ISRJ components. Simulation results demonstrate that the proposed method effectively overcomes the ISRJ under different modulation modes with almost no loss of signal energy. When the jamming-to-signal ratio is 9 dB, the method boosts the signal-to-jamming ratio by 30 dB after jamming suppression, ensuring robust target detection.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"234 ","pages":"Article 109994"},"PeriodicalIF":3.4,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143776395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

High-dimensional false discovery rate control for dependent variables 因变量的高维错误发现率控制

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-03-15 DOI: 10.1016/j.sigpro.2025.109990

Jasin Machkour , Michael Muma , Daniel P. Palomar

{"title":"High-dimensional false discovery rate control for dependent variables","authors":"Jasin Machkour , Michael Muma , Daniel P. Palomar","doi":"10.1016/j.sigpro.2025.109990","DOIUrl":"10.1016/j.sigpro.2025.109990","url":null,"abstract":"<div><div>Algorithms that ensure reproducible findings from large-scale, high-dimensional data are pivotal in numerous signal processing applications. In recent years, multivariate false discovery rate (FDR) controlling methods have emerged, providing guarantees even in high-dimensional settings where the number of variables surpasses the number of samples. However, these methods often fail to reliably control the FDR in the presence of highly dependent variable groups, a common characteristic in fields such as genomics and finance. To tackle this critical issue, we introduce a novel framework that accounts for general dependency structures. Our proposed dependency-aware T-Rex selector integrates hierarchical graphical models within the T-Rex framework to effectively harness the dependency structure among variables. Leveraging martingale theory, we prove that our variable penalization mechanism ensures FDR control. We further generalize the FDR-controlling framework by stating and proving a clear condition necessary for designing both graphical and non-graphical models that capture dependencies. Numerical experiments and a breast cancer survival analysis use-case demonstrate that the proposed method is the only one among the state-of-the-art benchmark methods that controls the FDR and reliably detects genes that have been previously identified to be related to breast cancer. An open-source implementation is available within the R package TRexSelector on CRAN.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"234 ","pages":"Article 109990"},"PeriodicalIF":3.4,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A state-of-the-art review on acoustic preservation of historical worship spaces through auralization 通过听觉化对历史敬拜空间的声学保护的最新评述

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-03-15 DOI: 10.1016/j.sigpro.2025.109992

Hannes Rosseel, Toon van Waterschoot

引用次数: 0

Pulse processing — Overview and challenges 脉冲处理-概述和挑战

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-03-13 DOI: 10.1016/j.sigpro.2025.109978

Jonathan H. Manton

引用次数: 0

Frequency offset deception velocity-based method for discriminating between physical targets and active false targets 基于频率偏移欺骗速度的方法，用于区分物理目标和主动假目标

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-03-12 DOI: 10.1016/j.sigpro.2025.109977

Deyu Li, Siyi Yao, Yi Liao, Jian Yan, Yusheng Fu

{"title":"Frequency offset deception velocity-based method for discriminating between physical targets and active false targets","authors":"Deyu Li, Siyi Yao, Yi Liao, Jian Yan, Yusheng Fu","doi":"10.1016/j.sigpro.2025.109977","DOIUrl":"10.1016/j.sigpro.2025.109977","url":null,"abstract":"<div><div>The discrimination of false targets by multistatic radar utilizing data-level fusion is contingent upon the differences in spatial information observed by receivers of different orientations. Nevertheless, if the target is situated in the far field, the jamming discrimination performance of multistatic radar is limited by the baseline distance of the receivers. To address this challenge, this paper designs a multistatic frequency diversity radar to mislead the carrier frequency estimation of the target jammer. This scheme introduces a difference in spectral information to the spatial information of the multistatic radar, thereby enhancing the jamming discrimination performance. In light of the above, we propose a frequency offset deception velocity-based (FODVB) method to discriminate active false targets. The method effectively fuses the spatial and frequency information to discriminate the false targets accurately and applies to multi-target scenarios. Furthermore, an optimal frequency selection strategy based on target orientation information is proposed to achieve the optimal discrimination performance of the FODVB method. The effectiveness of the proposed method is validated through Monte Carlo simulations.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"234 ","pages":"Article 109977"},"PeriodicalIF":3.4,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143628569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Low interactive direct position determination of radio emitters with hybrid measurements 混合测量无线电发射体的低交互直接位置测定

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-03-11 DOI: 10.1016/j.sigpro.2025.109987

Ming-Yi You , Lin Gao , Yun-Xia Ye , Wei Wang

{"title":"Low interactive direct position determination of radio emitters with hybrid measurements","authors":"Ming-Yi You , Lin Gao , Yun-Xia Ye , Wei Wang","doi":"10.1016/j.sigpro.2025.109987","DOIUrl":"10.1016/j.sigpro.2025.109987","url":null,"abstract":"<div><div>This paper proposes a direct position determination (DPD) method for stationary and moving non-cooperative sources. Employing an unbalanced group of measurements consisting of uncompressed measurements at the central receiver and compressed measurements from all other auxiliary receivers, the method estimates the source position directly in the hybrid measurement domain without original signal recovering, where the compressing matrix is not restricted to any specific form. A block coordinate descent (BCD)-like iterative algorithm is proposed to handle the high-dimensional optimization problem of joint position and velocity estimation for moving emitters, where a generalized cross ambiguity function (GCAF) is proposed to extract the time-differences-of-arrival (TDOA) parameters from the hybrid measurements to initialize the iteration process. In addition, the hybrid measurements-based Cramér–Rao lower bound (CRLB) for emitter position is derived for performance evaluation. Several numerical case studies are carried out to evaluate the effectiveness of the proposed DPD method as well as the proposed GCAF. The proposed method is expected to extend the applicability of compressive sensing (CS)-based DPD to cases where there is relative radial motion between the source.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"234 ","pages":"Article 109987"},"PeriodicalIF":3.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0