Digital Signal Processing最新文献_第5页

CRAPA - A measurement-preprocessing algorithm based on correntropy and attention mechanism 一种基于相关熵和注意机制的测量预处理算法

IF 3 3区工程技术

Digital Signal Processing Pub Date : 2025-09-09 DOI: 10.1016/j.dsp.2025.105600

Xiaohan Yu , Qin Zhang , Kuiwu Wang , Xiaolong Hu

{"title":"CRAPA - A measurement-preprocessing algorithm based on correntropy and attention mechanism","authors":"Xiaohan Yu , Qin Zhang , Kuiwu Wang , Xiaolong Hu","doi":"10.1016/j.dsp.2025.105600","DOIUrl":"10.1016/j.dsp.2025.105600","url":null,"abstract":"<div><div>In complex environments, non-Gaussian noise leads to the accumulation of state estimation deviations in traditional Kalman filter (KF), severely degrading the robustness of target tracking systems. Although existing methods optimize filtering performance through noise statistical modeling or robust loss functions, they are still limited by issues such as fixed parameters, model mismatch, and high computational complexity. This paper proposes a measurement preprocessing algorithm based on correntropy and residual attention mechanism (CRAPA). By calculating dynamic weights through the Gaussian kernel correntropy of historical residuals and current residuals within a sliding window, it adaptively identifies and suppresses abnormal measurements. CRAPA adopts modular architecture, combining feedforward suppression mechanisms to block noise propagation. While retaining the optimality of the KF framework, it achieves efficient abnormal detection with relatively low complexity. Simulation experiments show that under Gaussian-mixture noise and Gaussian impulse hybrid noise scenarios, CRAPA significantly reduces the mean square error of KF. Its dynamic window mechanism responds faster than noise statistical modeling algorithms, and its tracking accuracy is comparable to that of Huber-KF, with stronger parameter adaptability. This validates the robustness and tracking performance of CRAPA in non-Gaussian noise, especially in impulse noise environments, providing theoretical support for subsequent extensions to maneuvering target scenarios and deep learning integration.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"168 ","pages":"Article 105600"},"PeriodicalIF":3.0,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Infrared and visible image fusion based on one–dimensional guided filtering and cross–modal weight perception 基于一维引导滤波和跨模态权重感知的红外与可见光图像融合

IF 3 3区工程技术

Digital Signal Processing Pub Date : 2025-09-09 DOI: 10.1016/j.dsp.2025.105593

Yongsong Li , Yuezhen Jing , Zhengzhou Li , Abubakar Siddique

{"title":"Infrared and visible image fusion based on one–dimensional guided filtering and cross–modal weight perception","authors":"Yongsong Li , Yuezhen Jing , Zhengzhou Li , Abubakar Siddique","doi":"10.1016/j.dsp.2025.105593","DOIUrl":"10.1016/j.dsp.2025.105593","url":null,"abstract":"<div><div>Infrared and visible image fusion aims to obtain a clear image with rich information by incorporating the salient target information in infrared image and the rich textures in visible image. Existing fusion methods encounter some challenges, such as unclear target, low contrast, poor visual effect, and lose texture details. To solve above problems, an effective fusion method based on one–dimensional guided filtering (1DGF) and cross–modal weight perception is proposed. Firstly, the original images are decomposed into a series of base layers and detail layers along row and column directions by the 1DGF. Secondly, a cross–modal saliency weighting (CSW) based on sequential morphological reconstruction is developed for base layer fusion to match the human visual characteristics. Simultaneously, a cross–modal edge aware weighting (CEAW) based on relative local variance is constructed with a noise discrimination rule is incorporated for detail layer fusion, so as to minimize noise interference while enhancing details. After that, the fused image can be reconstructed from the generated base layer and detail layer. Results prove that this method is better than several existing methods according to visual and quantitative comparisons in infrared and visible image groups of diverse scenarios.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"168 ","pages":"Article 105593"},"PeriodicalIF":3.0,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Underwater passive sonar fusion detection based on sensor bias estimation and classification 基于传感器偏差估计与分类的水下被动声呐融合检测

IF 3 3区工程技术

Digital Signal Processing Pub Date : 2025-09-09 DOI: 10.1016/j.dsp.2025.105596

Qixiang Niu , Wentao Shi , Qunfei Zhang , Dongzhe Zhang

{"title":"Underwater passive sonar fusion detection based on sensor bias estimation and classification","authors":"Qixiang Niu , Wentao Shi , Qunfei Zhang , Dongzhe Zhang","doi":"10.1016/j.dsp.2025.105596","DOIUrl":"10.1016/j.dsp.2025.105596","url":null,"abstract":"<div><div>Passive sonar is crucial for underwater target detection but often experiences reduced localization accuracy due to sensor biases and positional deviations caused by environmental factors. Traditional approaches struggle to effectively address these biases and also lack an integrated analysis of bias estimation, sensor classification, and fusion algorithms. To address this issue, this paper proposes a bias estimation-classification-fusion localization (BECFL) algorithm, integrating bias estimation, sensor classification, and adaptive fusion weighting. Within the BECFL framework, dynamic stochastic models are first developed to characterize underwater target motion, sensor biases, and multipath fading channels. Sensor biases are then estimated using maximum likelihood estimation (MLE) based on multiple sensor observations. Sensors are subsequently classified through an improved expectation-maximization (EM) algorithm, iteratively refining the classification parameters. A variable step-size weighting fusion approach is applied, reducing the impact of sensor biases on localization results. Simulations demonstrate that, compared to existing methods, the BECFL algorithm improves localization accuracy and maintains robust performance even under significant sensor bias, data loss, false alarms, and missed detections. Additionally, analyses of actual underwater data confirm the practical applicability of the proposed algorithm for passive sonar detection and localization in underwater environments.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"168 ","pages":"Article 105596"},"PeriodicalIF":3.0,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145265496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 novel feature extraction framework based on periodic features for human activity recognition using wearable sensor data 一种基于周期特征的可穿戴传感器人体活动识别特征提取框架

IF 3 3区工程技术

Digital Signal Processing Pub Date : 2025-09-08 DOI: 10.1016/j.dsp.2025.105584

Wenhang Su , Chengjun Wang , Jiabao Li , Zhipeng Yu , Li Jin

{"title":"A novel feature extraction framework based on periodic features for human activity recognition using wearable sensor data","authors":"Wenhang Su , Chengjun Wang , Jiabao Li , Zhipeng Yu , Li Jin","doi":"10.1016/j.dsp.2025.105584","DOIUrl":"10.1016/j.dsp.2025.105584","url":null,"abstract":"<div><div>Human Activity Recognition (HAR) is widely applied in various fields, where its accuracy and robustness are crucial. However, existing methods primarily focus on extracting spatiotemporal features, failing to fully utilize the complex periodic features present in human activities. Human behavior typically involves significant periodic patterns. Failure to effectively capture these periodic features can limit the model’s performance in handling complex behaviors, thereby affecting the accuracy and generalization ability of recognition. To address this issue, this paper proposes a network framework for periodic feature extraction—Time-FWTNet. This network integrates Fourier Transform to extract global periodic features. The FWT-Block module is designed to decompose global features and extract local periodic features, enabling the HAR method to simultaneously focus on both global and local periodic characteristics. Additionally, we propose Freq-CM to decompose high-frequency and low-frequency components for targeted feature learning, while expanding the receptive field with small convolution kernels. To verify the performance of Time-FWTNet, we conduct experiments on a constructed dataset as well as three public datasets. The experimental results show that Time-FWTNet achieves average accuracies of 98.89 %, 98.81 %, 98.76 %, and 98.72 % on the AUST-HAR, USC-HAD, UCL-HAPT, and PAMAP2 datasets, respectively.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"168 ","pages":"Article 105584"},"PeriodicalIF":3.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Waveform design for detection and jamming integrated multifunctional radar 探测与干扰综合多功能雷达的波形设计

IF 3 3区工程技术

Digital Signal Processing Pub Date : 2025-09-08 DOI: 10.1016/j.dsp.2025.105570

Kaiwei Wang , Jingwei Xu , Guisheng Liao , Yuhong Zhang , Keyi Wang

{"title":"Waveform design for detection and jamming integrated multifunctional radar","authors":"Kaiwei Wang , Jingwei Xu , Guisheng Liao , Yuhong Zhang , Keyi Wang","doi":"10.1016/j.dsp.2025.105570","DOIUrl":"10.1016/j.dsp.2025.105570","url":null,"abstract":"<div><div>It is increasingly demanded that multifunctional radars (MFRs) address electromagnetic compatibility issues caused by a growing number of devices mounted on the same platform. In this paper, we investigate a detection and jamming integrated MFR (DJI-MFR) system capable of operating simultaneously in target detection and electronic warfare (EW) modes. Waveform design poses a significant challenge for DJI-MFR, as it must emulate hostile radar waveforms to achieve jamming while concealing probing waveforms for effective detection. The proposed waveform design method combines a probing waveform component with a jamming waveform component. An integrated waveform with both non-constant and constant modulus properties is designed to accommodate transmitters operating in both linear and saturated states. To ensure detection performance, the autocorrelation of the probing waveform is constrained to a minimum requirement, whereas the cross-correlation between probing and jamming waveforms is restricted below a maximum tolerance threshold. This problem is formulated as an optimization framework and solved using a coordinate descent (CD) algorithm. Detection performance is evaluated by analyzing the signal-to-interference-and-noise ratio (SINR), while jamming effectiveness is quantified through the jamming-to-noise ratio (JNR). Numerical simulations demonstrate the efficacy of the proposed waveform design method for DJI-MFR.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"168 ","pages":"Article 105570"},"PeriodicalIF":3.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145046055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 automatic generation control subject to ramp-rate-limits: Anytime feasibility and uniform network-connectivity 受斜坡速率限制的分布式自动发电控制：随时可行，网络连通均匀

IF 3 3区工程技术

Digital Signal Processing Pub Date : 2025-09-08 DOI: 10.1016/j.dsp.2025.105576

Mohammadreza Doostmohammadian , Hamid R. Rabiee

{"title":"Distributed automatic generation control subject to ramp-rate-limits: Anytime feasibility and uniform network-connectivity","authors":"Mohammadreza Doostmohammadian , Hamid R. Rabiee","doi":"10.1016/j.dsp.2025.105576","DOIUrl":"10.1016/j.dsp.2025.105576","url":null,"abstract":"<div><div>This paper considers automatic generation control over an information-sharing network of communicating generators as a multi-agent system. The optimization solution is distributed among the agents based on information consensus algorithms, while addressing the generators' ramp-rate-limits (RRL). This is typically ignored in the existing linear/nonlinear optimization solutions but they exist in real-time power generation scenarios. Without addressing the RRL, the generators cannot follow the assigned rate of generating power by the optimization algorithm; therefore, the existing solutions may not necessarily converge to the exact optimal cost or may lose feasibility in practice. The proposed solution in this work addresses the ramp-rate-limit constraint along with the box constraint (limits on the generated powers) and the coupling-constraint (generation-demand balance) at all iteration times of the algorithm. The latter is referred to as the anytime feasibility and implies that at every termination point of the algorithm, the balance between the demand and generated power holds. To improve the convergence rate of the algorithm we further consider internal signum-based nonlinearity. We also show that our solution can tolerate communication link removal. This follows from the uniform-connectivity assumption on the communication network.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"168 ","pages":"Article 105576"},"PeriodicalIF":3.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Asymmetric and discriminative hashing for cross-modal retrieval 跨模态检索的非对称和判别哈希

IF 3 3区工程技术

Digital Signal Processing Pub Date : 2025-09-07 DOI: 10.1016/j.dsp.2025.105595

Linna Hao , Hengkun Liang , Jun Yu , Zhenqiu Shu

{"title":"Asymmetric and discriminative hashing for cross-modal retrieval","authors":"Linna Hao , Hengkun Liang , Jun Yu , Zhenqiu Shu","doi":"10.1016/j.dsp.2025.105595","DOIUrl":"10.1016/j.dsp.2025.105595","url":null,"abstract":"<div><div>Cross-modal hashing has garnered substantial interest in the domain of information retrieval owing to its advantages in storage and computation. However, prevalent cross-modal hashing techniques frequently struggle to adequately exploit the discriminative information inherent in modalities, leading to suboptimal performance in retrieval tasks. Additionally, the symmetric factorization methods encounters tricky optimization problems and information loss when solving discrete variables. To address these limitations, we propose an Asymmetric and Discriminative Cross-modal Hashing(ADCH) method. On the one hand, ADCH incorporates a projection learning module with kernel discriminant analysis to find a discriminative common subspace. On the other hand, an asymmetric hash learning approach that preserves the pairwise label distance relations is developed to enhance the discriminative power of the learned hash functions. The extensive experiments were carried out on four benchmark datasets and the experimental results demonstrate that ADCH achieves significant improvements on retrieval precision and outperforms state-of-the-art cross-modal hashing methods.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"168 ","pages":"Article 105595"},"PeriodicalIF":3.0,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

AACRNet: Ambiguity-aware change refinement network for remote sensing images change detection 基于模糊感知的遥感图像变化细化网络

IF 3 3区工程技术

Digital Signal Processing Pub Date : 2025-09-07 DOI: 10.1016/j.dsp.2025.105594

Junwei Li, Rihai Lai, Shuaiao Li, Peng Yu, Xuefeng Ma, Hongtai Yao

{"title":"AACRNet: Ambiguity-aware change refinement network for remote sensing images change detection","authors":"Junwei Li, Rihai Lai, Shuaiao Li, Peng Yu, Xuefeng Ma, Hongtai Yao","doi":"10.1016/j.dsp.2025.105594","DOIUrl":"10.1016/j.dsp.2025.105594","url":null,"abstract":"<div><div>Change detection is a fundamental task in remote sensing image analysis. Despite the promising results achieved by recent deep learning-based methods, existing approaches still struggle with ambiguous cases, particularly in scenarios with high visual similarity to complex background noise. Such visual ambiguity often results in semantic confusion and erroneous predictions. However, few methods have explicitly addressed this challenge. In this paper, we propose an ambiguity-aware change refinement network (AACRNet) to tackle this issue. Specifically, a Siamese backbone network is utilized to extract multi-level feature representations from bitemporal images. At each hierarchical level, a temporal difference fusion module (TDFM) is introduced to dynamically establish spatiotemporal relationships, capture global change information, and generate difference features. To mitigate semantic discrepancies between adjacent hierarchical difference features and efficiently locate key change regions, we incorporate a semantic aggregation module (SAM) to integrate global semantic information. Furthermore, we propose a focusing refinement module (FRM) to explicitly model ambiguous regions, introducing a novel strategy that exploits global semantic information to extract and distinguish interference signals within these ambiguous regions. By progressively refining cross-layer features, the FRM enhances semantic consistency and reduces false predictions in such areas. Extensive experiments on the WHU-CD, LEVIR-CD, and SYSU-CD datasets indicate that AACRNet outperforms other state-of-the-art (SOTA) change detection methods, achieving superior accuracy and robustness.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"168 ","pages":"Article 105594"},"PeriodicalIF":3.0,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Design and performance analysis for adaptive detection of polarimetric radar in Gaussian environment and structured interference 高斯环境和结构干扰下极化雷达自适应检测的设计与性能分析

IF 3 3区工程技术

Digital Signal Processing Pub Date : 2025-09-06 DOI: 10.1016/j.dsp.2025.105582

Hongzhi Guo, Haoqi Wu, Zhihang Wang, Zishu He, Ziyang Cheng

引用次数: 0

Construction of a new Lorenz-like system with cubic nonlinearity and its application in weak signal detection 一类新的三次非线性类洛伦兹系统的构造及其在弱信号检测中的应用

IF 3 3区工程技术

Digital Signal Processing Pub Date : 2025-09-06 DOI: 10.1016/j.dsp.2025.105601

Xiaoli Yan , Zhetian Wang , Meng Yuan , Shiliang Wang , Lide Fang , Shiyu Liu

{"title":"Construction of a new Lorenz-like system with cubic nonlinearity and its application in weak signal detection","authors":"Xiaoli Yan , Zhetian Wang , Meng Yuan , Shiliang Wang , Lide Fang , Shiyu Liu","doi":"10.1016/j.dsp.2025.105601","DOIUrl":"10.1016/j.dsp.2025.105601","url":null,"abstract":"<div><div>To investigate the application value of the Lorenz system in weak signal detection for rolling bearing vibrations, this study innovatively proposes an improved Lorenz system model incorporating a cubic nonlinear term. This improvement not only enhances the system's performance in weak signal detection but also provides new research perspectives for a deeper understanding of nonlinear dynamic behaviors. The study focuses on analyzing the influence mechanism of the cubic nonlinear term on the system's chaotic characteristics and systematically examines the practical application effectiveness of this improved model in weak signal detection. Under constant parameter conditions, a systematic sensitivity analysis was conducted to evaluate the dynamical implications of introducing cubic nonlinearities into the first two governing equations of the system. Our research reveals that as one of the control parameters decreases, the system exhibits a singular degenerate heteroclinic cycles structure, whose collapse process establishes a crucial evolutionary pathway toward chaotic states. In the end, by utilizing the transient chaotic characteristics of the novel Lorenz-like system with cubic terms, we propose a method capable of detecting weak signals in strong noise environments and performing mechanical fault diagnosis. Its effectiveness has been verified through both simulations and experimental validation.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"168 ","pages":"Article 105601"},"PeriodicalIF":3.0,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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