Signal Processing最新文献

Sparse coarray manifold separation for efficient cellular localization using coprime array 稀疏共阵流形分离在元胞定位中的应用

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-06-21 DOI: 10.1016/j.sigpro.2025.110157

Shengheng Liu , Yonghe Shang , Wang Zheng , Peng Liu , Yongming Huang

引用次数: 0

A fast Poisson labeled multi-Bernoulli filter for extended object tracking using belief propagation 基于信念传播的扩展目标跟踪快速泊松标记多伯努利滤波器

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-06-21 DOI: 10.1016/j.sigpro.2025.110156

Runyan Lyu , Liang Hao , Litao Zheng , Yunze Cai

{"title":"A fast Poisson labeled multi-Bernoulli filter for extended object tracking using belief propagation","authors":"Runyan Lyu , Liang Hao , Litao Zheng , Yunze Cai","doi":"10.1016/j.sigpro.2025.110156","DOIUrl":"10.1016/j.sigpro.2025.110156","url":null,"abstract":"<div><div>This paper addresses the multiple extended object tracking problem to enhance tracking accuracy and efficiency while ensuring track continuity. We propose a novel parameter-based PLMB-BP filter that integrates random finite set (RFS) and belief propagation (BP) methods. Poisson and labeled multi-Bernoulli (PLMB) RFSs are employed to model the states of newborn objects and multiple extended objects. By leveraging their advantages, the proposed filter simultaneously ensures track continuity and enhances birth model flexibility. Furthermore, the parameter-based BP is implemented for the marginal probability density function of object states and association variables. Inspired by fixed-point iteration, this implementation achieves joint estimation of measurement rate, kinematic state, and extent state for multiple extended objects, while maintaining superior real-time capability. Simulations are performed for closely spaced multiple extended objects with ellipsoidal shapes. The results demonstrate the enhanced tracking performance and the superior real-time capability of the proposed filter.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"238 ","pages":"Article 110156"},"PeriodicalIF":3.4,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144338869","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

Improving waveform for FDA-MIMO-based DFRC systems by collaborating modulation and optimization 通过协同调制和优化改善基于fda - mimo的DFRC系统的波形

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-06-21 DOI: 10.1016/j.sigpro.2025.110158

Langhuan Geng, Yong Li, Limeng Dong, Wei Cheng, Qianlan Kou, Yumei Tan

{"title":"Improving waveform for FDA-MIMO-based DFRC systems by collaborating modulation and optimization","authors":"Langhuan Geng, Yong Li, Limeng Dong, Wei Cheng, Qianlan Kou, Yumei Tan","doi":"10.1016/j.sigpro.2025.110158","DOIUrl":"10.1016/j.sigpro.2025.110158","url":null,"abstract":"<div><div>The dual-function radar-communication (DFRC) system based on frequency diverse array multiple-input multiple-output (FDA-MIMO) has garnered significant attention. However, designing a promising integrated waveform for an FDA-MIMO-based DFRC system remains a challenge due to the limitations inherent in existing modulation and optimization methods. This paper proposes a new hybrid index modulation (HIM) method that dynamically selects communication subpulses and frequency offsets to transmit information in a flexible and efficient manner, thereby achieving high data rates and low bit error rates. Building upon the proposed HIM, we minimize the beampattern integrated sidelobe level to enhance detection capability, while accounting for multiple practical constraints to ensure that the optimized integrated waveform is hardware-compatible and meets communication requirements. Furthermore, we decompose the formulated problem by using the strong coupling-based alternating direction method of multipliers, and introduce progressive approximation-guided optimization and alternating optimization with successive convex approximation to obtain the optimal frequency offset unit and waveform. Simulation results demonstrate that the proposed integrated waveform design method outperforms existing approaches in terms of both radar and communication performance.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"238 ","pages":"Article 110158"},"PeriodicalIF":3.4,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144366604","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

Impact of erroneous reporting on heterogeneous cognitive radio networks using improved primary user detection 使用改进的主用户检测对异构认知无线网络错误报告的影响

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-06-19 DOI: 10.1016/j.sigpro.2025.110150

Beulah Sujan Karumanchi, Narasimha Rao Banavathu

{"title":"Impact of erroneous reporting on heterogeneous cognitive radio networks using improved primary user detection","authors":"Beulah Sujan Karumanchi, Narasimha Rao Banavathu","doi":"10.1016/j.sigpro.2025.110150","DOIUrl":"10.1016/j.sigpro.2025.110150","url":null,"abstract":"<div><div>This paper examines the efficacy of the heterogeneous cognitive radio (CR) network, where heterogeneity refers to different sensing signal-to-noise ratios among CR users. The primary purpose is to improve signal detection accuracy in the presence of reporting channel errors using the improved energy detector and the soft-information fusion scheme. The major contribution of this work is the derivation of generalized expressions for false alarm and missed detection probabilities, applicable to a wide range of existing and new scenarios. Further, we proposed a generalized optimization framework for soft-information fusion to minimize the system’s decision error probability. This framework demonstrates that several existing and new optimization problems can be regarded as special cases. This work also proposes a framework to determine the minimum number of CR users required in the CR network to achieve the system’s target decision error probability. Theoretical findings are validated through numerical results under both heterogeneous and homogeneous configurations. The results indicate that the heterogeneous configuration yields a lower decision error probability compared to the homogeneous model. Furthermore, the theoretical outcomes are compared with Monte Carlo simulations, showing close alignment. This alignment confirms the validity of the proposed CR network for practical implementation.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"238 ","pages":"Article 110150"},"PeriodicalIF":3.4,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322067","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

An event-triggered distributed Mδ-GLMB filter 事件触发的分布式m - δ- glmb滤波器

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-06-17 DOI: 10.1016/j.sigpro.2025.110149

Yue Li , Lin Gao , Giorgio Battistelli , Luigi Chisci , Yi Sun , Ping Wei

{"title":"An event-triggered distributed Mδ-GLMB filter","authors":"Yue Li , Lin Gao , Giorgio Battistelli , Luigi Chisci , Yi Sun , Ping Wei","doi":"10.1016/j.sigpro.2025.110149","DOIUrl":"10.1016/j.sigpro.2025.110149","url":null,"abstract":"<div><div>The marginalized <span><math><mi>δ</mi></math></span>-generalized labeled multi-Bernoulli (M<span><math><mi>δ</mi></math></span>-GLMB) filter has demonstrated its effectiveness in multi-target tracking, and fusion rules have been proposed for M<span><math><mi>δ</mi></math></span>-GLMB densities so as to allow its use in distributed multi-target tracking applications. However, the M<span><math><mi>δ</mi></math></span>-GLMB density is formed based on hypotheses whose numbers increase exponentially with respect to the cardinality of the label set, thus imposing a heavy communication burden on the sensor network. To overcome this problem, two event-triggered (ET) strategies are devised in this paper for fusion of M<span><math><mi>δ</mi></math></span>-GLMB densities, which are able to significantly reduce the data exchange rate at the price of a slight performance loss. Specifically, a method for tuning the hypothesis weights is proposed for the ET strategy so as to guarantee the normalization of the M<span><math><mi>δ</mi></math></span>-GLMB density. The effectiveness of the proposed methods is verified via simulation results.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"238 ","pages":"Article 110149"},"PeriodicalIF":3.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331462","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

Multi-view Clustering based on Doubly Stochastic Graph 基于双随机图的多视图聚类

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-06-17 DOI: 10.1016/j.sigpro.2025.110144

Nian Wang , Zhigao Cui , Aihua Li , Rong Wang , Feiping Nie

{"title":"Multi-view Clustering based on Doubly Stochastic Graph","authors":"Nian Wang , Zhigao Cui , Aihua Li , Rong Wang , Feiping Nie","doi":"10.1016/j.sigpro.2025.110144","DOIUrl":"10.1016/j.sigpro.2025.110144","url":null,"abstract":"<div><div>Most Multi-view Graph-based Clustering (MGC) models always obtain suboptimal performance since the necessary symmetry of graph is ignored during the process of graph fusion. To solve the problem, we propose Multi-view Clustering based on Doubly Stochastic Graph (MCDSG). Our MCDSG precalculates Single-view Similarity Graphs (SSGs) and then fuses them into a consensus one with doubly stochastic (non-negative, sum-to-one and symmetry) constraints, directly providing clustering results by its connectivity. For optimization, a novel and easy-understanding Augmented Lagrangian Method (ALM) is proposed to substitute the widely used Von-Neumann Successive Projection (VNSP) method, which simultaneously optimizes all the doubly stochastic conditions to the optimal solution. To verify the robustness to noisy data sets, we propose a pipeline to add noise to the key features of face images and obtain a two-view data set termed NoisedORL. Experiments on both synthetic data sets and real benchmarks show that our MCDSG achieves SOTA clustering performance against nine methods. Code will be published at <span><span>https://github.com/NianWang-HJJGCDX/MCDSG</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"238 ","pages":"Article 110144"},"PeriodicalIF":3.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331463","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

FDA-MIMO radar detecting target embedded in mainlobe deceptive jamming plus Gaussian noise FDA-MIMO雷达探测嵌入在主瓣欺骗性干扰加高斯噪声中的目标

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-06-17 DOI: 10.1016/j.sigpro.2025.110147

Bang Huang , Wen-Qin Wang , Ping Li , Jiangwei Jian , Libing Huang , Wenkai Jia , Mingcheng Fu

{"title":"FDA-MIMO radar detecting target embedded in mainlobe deceptive jamming plus Gaussian noise","authors":"Bang Huang , Wen-Qin Wang , Ping Li , Jiangwei Jian , Libing Huang , Wenkai Jia , Mingcheng Fu","doi":"10.1016/j.sigpro.2025.110147","DOIUrl":"10.1016/j.sigpro.2025.110147","url":null,"abstract":"<div><div>In this paper, we address the challenge of detecting targets embedded in a mainlobe deceptive jamming environment, compounded by Gaussian noise, for the frequency diverse array multiple input multiple output (FDA-MIMO) radar. Unlike conventional MIMO and/or phased-array (PA) radar systems, FDA-MIMO radar leverages additional range information, presenting a promising avenue for mitigating mainlobe deception interference. Our work begins by establishing a waveform-orthogonal FDA-MIMO radar received signal model under Gaussian noise, which encompasses thermal noise, suppression interference, and clutter after secondary range dependence compensation. Subsequently, we formulate the problem of binary hypothesis signal detection in the presence of mainlobe deception interference and training data within a detection scenario. To address this detection problem, we propose two adaptive detectors based on the one-step and two-step general likelihood ratio test (GLRT) criteria, denoted as OGLRT and TGLRT, respectively. Numerical simulation results demonstrate that our proposed detectors exhibit the constant false alarm rate (CFAR) property against the noise covariance matrix. Moreover, the performance of our proposed methods surpasses that of existing subspace detectors, with OGLRT exhibiting the best detection performance. As the frequency offsets for FDA-MIMO radar decrease, the performance of all detectors gradually deteriorates until they no longer retain target detection capabilities. This observation implies that, in the mainlobe deception interference environment considered in this paper, MIMO radar loses its ability to detect targets.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"238 ","pages":"Article 110147"},"PeriodicalIF":3.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322066","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

On the analysis and comparison between MPR and cartesian for TDOA localization MPR与直角坐标在TDOA定位中的分析与比较

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-06-16 DOI: 10.1016/j.sigpro.2025.110148

Yimao Sun , Tianyi Xing , Yanbin Zou , Yangbing Yang , Liangyin Chen

{"title":"On the analysis and comparison between MPR and cartesian for TDOA localization","authors":"Yimao Sun , Tianyi Xing , Yanbin Zou , Yangbing Yang , Liangyin Chen","doi":"10.1016/j.sigpro.2025.110148","DOIUrl":"10.1016/j.sigpro.2025.110148","url":null,"abstract":"<div><div>Modified polar representation (MPR) provides a unified mathematical framework for both point localization and direction finding in near-field and far-field scenarios. Although prior research has shown that MPR alleviates the range thresholding effect, which refers to the sudden degradation in localization accuracy when the source moves beyond a critical distance, a rigorous theoretical explanation and comprehensive comparison with the Cartesian representation (CR) are still lacking. This paper analyzes the advantages and limitations of MPR and CR for time difference of arrival (TDOA)-based localization under both known and unknown signal propagation speeds (SPS). While the Cramér–Rao lower bound (CRLB) and hybrid Bhattacharyya–Barankin bound (HBBB) have been studied previously for known-SPS scenarios in Wang and Ho (2017), we derive and analyze the HBBB under the unknown-SPS setting. HBBB provides a tighter analytical evaluation beyond the CRLB, so it can quantify the thresholding effect when the source is distant or noise is high. Furthermore, an analytical comparison based on the Hessian of the maximum likelihood (ML) cost function is performed to reveal why MPR is more noise-robust in far-field conditions, whereas CR performs better in the near field—findings supported by the HBBB. Additionally, the far-field case is investigated, establishing the equivalence of MPR with the conventional far-field model in estimating both angles and SPS. These results enhance the theoretical understanding of MPR and underscore its practical implications for localization and sensing applications.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"238 ","pages":"Article 110148"},"PeriodicalIF":3.4,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144366605","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

Trustworthy data recovery for incomplete multi-view learning 不完全多视图学习的可信数据恢复

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-06-16 DOI: 10.1016/j.sigpro.2025.110146

Huangyi Deng, Ningning Pan, Chuanqing Tang, Long Shi

{"title":"Trustworthy data recovery for incomplete multi-view learning","authors":"Huangyi Deng, Ningning Pan, Chuanqing Tang, Long Shi","doi":"10.1016/j.sigpro.2025.110146","DOIUrl":"10.1016/j.sigpro.2025.110146","url":null,"abstract":"<div><div>Incomplete multi-view learning has recently made progress towards more reliable decision-making. Existing methods mainly follow a two-step process: first, conducting data imputation, and then performing opinion aggregation based on evidential deep learning. Although these methods evaluate reliability in the final decision-making phase, they neglect leveraging uncertainty to guide high-quality data imputation. In this paper, we put forward a novel trusted framework termed as Trustworthy Data Recovery for Incomplete Multi-view Learning (TDR-IML) which enables trustworthy data imputation in an uncertain-supervision way. First, we obtain the <span><math><mi>k</mi></math></span>-nearest neighbor nodes of the incomplete data instance and construct a multivariate Gaussian distribution to model the missing data’s latent space. Then, we perform multiple samplings for the missing data and filter out low-quality samples whose uncertainty exceeds the average uncertainty of all the sampled data. In addition, we refine the opinion decoupling strategy to mitigate semantic ambiguity, thereby improving the extraction of both consistent and complementary opinions. We finally conduct experiments on real-world datasets to validate our model. The code is available on <span><span>https://github.com/ding6ding/TDR-IMV</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"238 ","pages":"Article 110146"},"PeriodicalIF":3.4,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144314611","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

MRAS: A matching robust adaptive steganography scheme for JPEG images over social networking platforms 社交网络平台上JPEG图像的匹配鲁棒自适应隐写方案

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-06-15 DOI: 10.1016/j.sigpro.2025.110172

Rakesh Kumar, Savina Bansal, R K Bansal

引用次数: 0