Signal Processing最新文献_第9页

Non-uniform sampling reconstruction for symmetrical NMR spectroscopy by exploiting inherent symmetry 利用固有对称性的对称核磁共振波谱非均匀采样重建

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-04-17 DOI: 10.1016/j.sigpro.2025.110057

Enping Lin , Ze Fang , Yuqing Huang , Yu Yang , Zhong Chen

引用次数: 0

Unimodular waveform design for ambiguity function shaping with spectral constraint via a manifold-based exact penalty method 基于流形精确惩罚法的频谱约束模糊函数整形的单模波形设计

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-04-17 DOI: 10.1016/j.sigpro.2025.110042

Xiangqing Xiao , Hua Wang , Jinfeng Hu , Xin Tai , Yongfeng Zuo , Huiyong Li , Kai Zhong , Dongxu An

{"title":"Unimodular waveform design for ambiguity function shaping with spectral constraint via a manifold-based exact penalty method","authors":"Xiangqing Xiao , Hua Wang , Jinfeng Hu , Xin Tai , Yongfeng Zuo , Huiyong Li , Kai Zhong , Dongxu An","doi":"10.1016/j.sigpro.2025.110042","DOIUrl":"10.1016/j.sigpro.2025.110042","url":null,"abstract":"<div><div>Unimodular waveform design for ambiguity function (AF) shaping is a key technology in radar system. Depending on whether the spectral compatibility of the waveform is considered or not, the problem can be categorized into two forms, the first without imposing spectral constraints and the second with spectral constraints. Both of them are complex quartic non-convex problems with constant modulus constraint (CMC), which are challenging to be solved. It is worth noting that the second one obtains more attention due to the improved spectral compatibility, but the involved inequality constraints further increase the difficulty of solving this problem. We note that the inequality constraints can be transformed into penalty terms of the objective function by constructing an exact penalty function. Additionally, the complex circle manifold (CCM) naturally satisfies the CMC, providing a suitable framework to address the resultant problem. Based on the above considerations, we propose a manifold-based exact penalty method (MEP). First, the inequality constraints are eliminated by constructing them as exact penalty terms of the objective function using an exact penalty function, which incorporates the constraints into the objective function. The resulting problem is then projected onto the CCM, transforming the problem into a complex quartic unconstrained optimization problem. Finally, a conjugate gradient (CG) method is derived to solve this unconstrained problem on the CCM. Simulation results confirm that compared to the methods in Wu et al. (2017), Alhujaili et al. (2020) and Zhang et al. (2023), the proposed method exhibits the following superior performance:(1) higher signal-to-interference ratios (SIR), (2) deeper notches and more precise control of the stopbands level of energy spectrum distribution (ESD), (3) stronger detection performance to weak targets.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"236 ","pages":"Article 110042"},"PeriodicalIF":3.4,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143848281","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

Radar target tracking based on motion characteristic and distribution pattern matching 基于运动特性和分布模式匹配的雷达目标跟踪

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-04-16 DOI: 10.1016/j.sigpro.2025.110034

Jingang Wang, Songbin Li, Ke Shi

{"title":"Radar target tracking based on motion characteristic and distribution pattern matching","authors":"Jingang Wang, Songbin Li, Ke Shi","doi":"10.1016/j.sigpro.2025.110034","DOIUrl":"10.1016/j.sigpro.2025.110034","url":null,"abstract":"<div><div>The mitigation of false alarm rates under real-world radar operating conditions represents a critical challenge in advancing radar target detection algorithms. This study proposes that utilizing multi-frame correlation information through radar target tracking constitutes an effective solution for suppressing false alarms. We present a radar target tracking methodology that integrates motion characteristic and distribution pattern matching, effectively leveraging multi-frame radar measurements and echo amplitude information. This approach enables false alarm reduction through trajectory consistency validation. Specifically, the method operates in two stages: First, state filtering based on motion characteristics is applied to predict potential candidate regions for previous detections within the current frame. Subsequently, within these candidate regions, a deep learning-based similarity evaluation framework employing a self-supervised Siamese network performs distribution pattern matching to establish optimal data associations. Experimental validation demonstrates that the proposed method achieves a 5.82% improvement in F1-score over benchmark algorithms, confirming its enhanced detection reliability and operational effectiveness.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"236 ","pages":"Article 110034"},"PeriodicalIF":3.4,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143851599","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

Dynamic and static Lagrange multiplier μ based Bayesian CP factorization with orthogonal factors: Theory and applications 基于动态和静态拉格朗日乘子μ的正交因子贝叶斯CP分解：理论与应用

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-04-16 DOI: 10.1016/j.sigpro.2025.110045

Jing Zhou, Zhichao Zhang

{"title":"Dynamic and static Lagrange multiplier μ based Bayesian CP factorization with orthogonal factors: Theory and applications","authors":"Jing Zhou, Zhichao Zhang","doi":"10.1016/j.sigpro.2025.110045","DOIUrl":"10.1016/j.sigpro.2025.110045","url":null,"abstract":"<div><div>The existing <span><math><mi>μ</mi></math></span>-Singular Value Decomposition (<span><math><mi>μ</mi></math></span>-SVD) denoising algorithm is capable of extracting gear fault information under strong noise conditions. However, this algorithm is only applicable to two-dimensional real-valued data and lacks a mechanism for implementing Automatic Rank Determination (ARD) in high-dimensional data. In this paper, a Bayesian and Tensor treatment of <span><math><mi>μ</mi></math></span>-SVD is employed to enable ARD. To further investigate the impact of the Lagrange multiplier <span><math><mi>μ</mi></math></span> on the proposed <span><math><mi>μ</mi></math></span>-variational Bayesian (<span><math><mi>μ</mi></math></span>-VB) algorithm, we examine its performance from both static and dynamic perspectives. Simulation results demonstrate that the <span><math><mi>μ</mi></math></span>-VB algorithm achieves ARD and performs well in noise reduction. Further the <span><math><mi>μ</mi></math></span>-VB algorithm performs better in wireless communication and linear image coding across numerical domains, tensor sizes, orthogonal factors, and <span><math><mi>μ</mi></math></span> settings.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"236 ","pages":"Article 110045"},"PeriodicalIF":3.4,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143848301","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

A puzzle matrix oriented secret sharing scheme for dual images with reversibility 一种面向解谜矩阵的可逆对偶图像秘密共享方案

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-04-15 DOI: 10.1016/j.sigpro.2025.110056

Yijie Lin , Jui‐Chuan Liu , Ching-Chun Chang , Chin‐Chen Chang

{"title":"A puzzle matrix oriented secret sharing scheme for dual images with reversibility","authors":"Yijie Lin , Jui‐Chuan Liu , Ching-Chun Chang , Chin‐Chen Chang","doi":"10.1016/j.sigpro.2025.110056","DOIUrl":"10.1016/j.sigpro.2025.110056","url":null,"abstract":"<div><div>Dual image reversible data hiding is a specialized research direction in the field of information security. Secret messages are embedded into the original image using an image signal processing algorithm for reversible data hiding. This process generates two share images, indistinguishable from the original image, and each distributed to different receivers. Only through collaboration between the receivers can the original image and secret message be fully recovered. A dual image reversible data hiding scheme is proposed based on a reference matrix. The pixel pairs from the two share images collaborate and result in embedding 6 bits using the puzzle matrix; thus, achieving an embedding rate of up to 1.5 bits per pixel. Experimental results demonstrate that the proposed scheme offers a high embedding capacity of up to 786,432 bits, good visual quality, and fast execution time. Compared to other state-of-the-art dual image reversible data hiding schemes, our advantage mainly lies in the larger embedding capacity. Compared with a previously proposed scheme with the same embedding capacity, our proposed scheme provides better visual quality and faster execution time.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"236 ","pages":"Article 110056"},"PeriodicalIF":3.4,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143851598","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

Distributed target tracking via UWSNs in the presence of multipath interference 存在多径干扰的UWSNs分布式目标跟踪

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-04-15 DOI: 10.1016/j.sigpro.2025.110041

Miaoyi Tang , Meiqin Liu , Senlin Zhang , Ronghao Zheng , Shanling Dong , Zhunga Liu

{"title":"Distributed target tracking via UWSNs in the presence of multipath interference","authors":"Miaoyi Tang , Meiqin Liu , Senlin Zhang , Ronghao Zheng , Shanling Dong , Zhunga Liu","doi":"10.1016/j.sigpro.2025.110041","DOIUrl":"10.1016/j.sigpro.2025.110041","url":null,"abstract":"<div><div>This article addresses the practical challenge of robust target tracking in a distributed network of underwater acoustic sensors operating under multipath interference. In underwater environments, multipath effects can cause received signals to interfere at the transducer, leading to the degradation of acoustic echoes. Consequently, this degradation introduces autocorrelated biases into the original measurements, thereby reducing tracking accuracy. To tackle this issue, we adopt a state-augmentation approach combined with Gaussian filtering to develop a novel distributed filter for a class of nonlinear time-varying systems. By augmenting both the target states and multipath-induced biases, the proposed method effectively handles the nonlinearities and interdependencies between state variables and multipath autocorrelation during the estimation process. We refer to the proposed method as DUKF-Mp and provide theoretical analysis to investigate the stability by verifying its stochastic boundedness. Numerical simulations validate the proposed method, showing that DUKF-Mp outperforms existing approaches in tracking accuracy and maintains robustness even under high levels of multipath interference.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"236 ","pages":"Article 110041"},"PeriodicalIF":3.4,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143851600","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

Elastic Supernet with Dynamic Training for JPEG steganalysis 基于动态训练的JPEG隐写分析弹性超网络

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-04-15 DOI: 10.1016/j.sigpro.2025.110038

Qiushi Li , Shunquan Tan , Bin Li , Jiwu Huang

{"title":"Elastic Supernet with Dynamic Training for JPEG steganalysis","authors":"Qiushi Li , Shunquan Tan , Bin Li , Jiwu Huang","doi":"10.1016/j.sigpro.2025.110038","DOIUrl":"10.1016/j.sigpro.2025.110038","url":null,"abstract":"<div><div>JPEG is the predominant image format across social networks, serving as a prime cover medium for image steganography. However, previous deep learning models for JPEG steganalysis heavily rely on domain expertise and tedious trial-and-error methods. In this paper, we propose a two-stage neural architecture search scheme for JPEG steganalysis, based on Elastic Supernet with Dynamic Training (ESDT). The method involves constructing a weight-nesting supernet, with the largest subnetwork pretrained on ImageNet (a large-scale visual database widely used for pretraining deep learning models) and finetuning for JPEG steganalysis. Based on this pretrained network, we aim to enhance the model’s performance in downstream tasks while reducing reliance on domain knowledge. A progressive shrinking strategy is introduced during supernet training to accommodate the need of elastic kernel sizes, depths, and widths. In the final stage, we utilize a performance predictor to identify the optimal subnetwork within the refined supernet. Extensive experiments showcase the method’s superiority over state-of-the-art methods in JPEG steganalysis, achieving lower computational costs and superior generalization performance.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"236 ","pages":"Article 110038"},"PeriodicalIF":3.4,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143848417","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

A robust TDOA localization method for researching upper bound on NLOS ranging error 一种研究NLOS测距误差上界的鲁棒TDOA定位方法

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-04-15 DOI: 10.1016/j.sigpro.2025.110040

Wenqi Shui , Mingjie Xiong , Wen Mai, Shuang Qin

{"title":"A robust TDOA localization method for researching upper bound on NLOS ranging error","authors":"Wenqi Shui , Mingjie Xiong , Wen Mai, Shuang Qin","doi":"10.1016/j.sigpro.2025.110040","DOIUrl":"10.1016/j.sigpro.2025.110040","url":null,"abstract":"<div><div>In time-difference-of-arrival (TDOA) localization, the accuracy of the robust convex optimization algorithm is significantly affected by the upper bound of non-line-of-sight (NLOS) ranging error. Some algorithms estimate NLOS ranging error and source coordinates together, which makes the NLOS upper bound seem unnecessary, but this often leads to lower localization accuracy. Therefore, it is crucial to establish a reasonable upper bound for the NLOS ranging error. However, existing robust optimization algorithms suffer a significant drawback when introducing upper bounds on NLOS ranging error: The assignment of the upper bound of the NLOS ranging error does not match the actual environment, leading to poor algorithm accuracy. To solve the rationality problem of the NLOS ranging error upper bound assignment, this paper innovatively proposes the NLOS error upper bound as an uncertain variable arising from NLOS variability. We then develop a robust optimization formulation using matrix transformations to optimize the upper bound. By applying techniques such as linearization and perturbation decomposition, we derive an optimal solution that adjusts the NLOS error upper bound. Simulations and experiments show that the proposed approach outperforms existing algorithms in terms of localization accuracy in NLOS environments.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"235 ","pages":"Article 110040"},"PeriodicalIF":3.4,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143838801","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

Persymmetric adaptive detection in the presence of subspace interference and clutter 存在子空间干扰和杂波时的不对称自适应检测

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-04-12 DOI: 10.1016/j.sigpro.2025.110023

Peiqin Tang , Jing Zhang , Can Huang , Hong Xu , Weijian Liu , Jun Liu

引用次数: 0

Fractional-order generalized complex correntropy algorithm for robust active noise control 分数阶广义复熵鲁棒有源噪声控制算法

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-04-12 DOI: 10.1016/j.sigpro.2025.110024

Yan Wang , Bingqing Lin , Yunhe Guan , Junhui Qian , Ying-Ren Chien , Guobing Qian

{"title":"Fractional-order generalized complex correntropy algorithm for robust active noise control","authors":"Yan Wang , Bingqing Lin , Yunhe Guan , Junhui Qian , Ying-Ren Chien , Guobing Qian","doi":"10.1016/j.sigpro.2025.110024","DOIUrl":"10.1016/j.sigpro.2025.110024","url":null,"abstract":"<div><div>In recent years, several adaptive filtering algorithms based on fractional-order calculation or correntropy criterion have been proposed. However, these algorithms suffer from rapid performance degradation when confronted with complex-valued non-Gaussian noise environments. To address this issue, this paper introduces the Filtered-X Fractional-Order Generalized Complex Correntropy (FxFOGCC) algorithm for complex domain Active Noise Control (ANC), utilizing the complex generalized Gaussian density (CGGD) function as the kernel function. Compared to existing adaptive ANC algorithms, the FxFOGCC algorithm demonstrates significantly improved robustness and effectiveness. Furthermore, to achieve a faster convergence rate and lower steady-state error, a Convex Combination scheme of the FxFOGCC (CFxFOGCC) algorithm is derived. The paper also presents stability analysis and computational complexity analysis for theoretical derivation. Finally, simulation results validate the superior performance of the proposed algorithms in scenarios involving complex-valued impulsive noise, a mixture of sinusoidal and impulsive noise, as well as real-world vehicle interior noise.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"235 ","pages":"Article 110024"},"PeriodicalIF":3.4,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143833437","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