IEEE Transactions on Signal Processing最新文献_第4页

Locally Differentially Private Online Federated Learning With Correlated Noise 基于相关噪声的局部差分私有在线联邦学习

IF 4.6 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-03-19 DOI: 10.1109/TSP.2025.3553355

Jiaojiao Zhang;Linglingzhi Zhu;Dominik Fay;Mikael Johansson

引用次数: 0

Invariance Theory for Radar Detection in Disturbance With Kronecker Product Covariance Structure—Part I: Gaussian Environment Kronecker积协方差结构干扰下雷达探测的不变性理论第一部分：高斯环境

IF 4.6 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-03-17 DOI: 10.1109/TSP.2025.3551204

Mengjiao Tang;Augusto Aubry;Antonio De Maio;Yao Rong

{"title":"Invariance Theory for Radar Detection in Disturbance With Kronecker Product Covariance Structure—Part I: Gaussian Environment","authors":"Mengjiao Tang;Augusto Aubry;Antonio De Maio;Yao Rong","doi":"10.1109/TSP.2025.3551204","DOIUrl":"10.1109/TSP.2025.3551204","url":null,"abstract":"This two-part paper addresses maximally invariant detection of range-spread targets embedded in disturbance characterized by an unknown Kronecker product-structured covariance matrix. Part I focuses on Gaussian interference, whereas Part II extends the study to compound-Gaussian, clutter-dominated environments. Leveraging the principle of invariance, this part identifies a suitable transformation group that effectively compresses the nuisance parameter space, ensuring the constant false alarm rate (CFAR) property (with respect to the Kronecker-structured covariance matrix) for all invariant detectors. A maximal invariant and an induced maximal invariant are subsequently derived, serving as powerful tools to guide the design of CFAR detectors. Some existing two-step CFAR detectors for this structured situation are expressed as functions of the derived maximal invariant. Furthermore, two novel detectors (whose CFARity holds true under some mild technical conditions) are devised: the former employs a pseudo-missing strategy by treating elements possibly contaminated by target signals as missing and utilizes an Expectation-Maximization algorithm to perform the covariance matrix estimation; the latter is based on the one-step generalized likelihood ratio test criterion and is implemented via an alternate optimization algorithm. Finally, their CFAR behavior and detection performance are assessed through numerical examples, demonstrating their superiority with respect to some conventional decision rules.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"1577-1593"},"PeriodicalIF":4.6,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143640562","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

Invariance Theory for Radar Detectionin Disturbance With Kronecker ProductCovariance Structure—Part II: CompoundGaussian Environment Kronecker积协方差结构干扰下雷达检测的不变性理论第二部分：复合高斯环境

IF 4.6 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-03-17 DOI: 10.1109/TSP.2025.3551199

Mengjiao Tang;Augusto Aubry;Antonio De Maio;Yao Rong

{"title":"Invariance Theory for Radar Detectionin Disturbance With Kronecker ProductCovariance Structure—Part II: CompoundGaussian Environment","authors":"Mengjiao Tang;Augusto Aubry;Antonio De Maio;Yao Rong","doi":"10.1109/TSP.2025.3551199","DOIUrl":"10.1109/TSP.2025.3551199","url":null,"abstract":"In this part of the paper, we consider the invariant framework and the novel constant false alarm rate (CFAR) detector design of Part I in compound Gaussian clutter. Specifically, the focus is on detecting range-spread targets embedded in compound Gaussian clutter that exhibits a Kronecker covariance structure. A suitable transformation group has been identified, ensuring that invariance implies the fully CFAR property, i.e., with respect to both the Kronecker covariance matrix and the texture. A maximal invariant is derived and used to gain insightful re-expressions of some established two-step adaptive CFAR detectors. At the stage of detector design, the pseudo-missing strategy proposed in Part I is adapted to the compound Gaussian case and then integrated into the test architectures to yield modified adaptive detectors. Furthermore, the one-step generalized likelihood ratio test is derived. Both detection strategies result in fully CFAR detectors under some mild technical conditions, as evidenced by their invariance with respect to the identified transformation group. For performance evaluation, their CFAR behavior and detection probability are assessed and analyzed across different experimental setups and signal models, highlighting the superior performance of the newly proposed detectors compared to some conventional counterparts and to those that do not leverage the prior (Kronecker) structure.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"1594-1610"},"PeriodicalIF":4.6,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143640847","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

Detection and Multiparameter Estimation for NLoS Targets: An RIS-Assisted Framework NLoS 目标的探测和多参数估计：RIS 辅助框架

IF 4.6 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-03-17 DOI: 10.1109/TSP.2025.3546991

Zhouyuan Yu;Xiaoling Hu;Chenxi Liu;Qin Tao;Mugen Peng

{"title":"Detection and Multiparameter Estimation for NLoS Targets: An RIS-Assisted Framework","authors":"Zhouyuan Yu;Xiaoling Hu;Chenxi Liu;Qin Tao;Mugen Peng","doi":"10.1109/TSP.2025.3546991","DOIUrl":"10.1109/TSP.2025.3546991","url":null,"abstract":"Reconfigurable intelligent surface (RIS) has the potential to enhance sensing performance, due to its capability of reshaping the echo signals. Different from the existing literature, which has commonly focused on RIS beamforming optimization, in this paper, we pay special attention to designing effective signal processing approaches to extract sensing information from RIS-reshaped echo signals. To this end, we investigate an RIS-assisted non-line-of-sight (NLoS) target detection and multi-parameter estimation problem in orthogonal frequency division multiplexing (OFDM) systems. To address this problem, we first propose a novel detection and direction estimation framework, including a low-overhead hierarchical codebook that allows the RIS to generate three-dimensional beams with adjustable beam direction and width, a delay spectrum peak-based beam training scheme for detection and direction estimation, and a beam refinement scheme for further enhancing the accuracy of the direction estimation. Then, we propose a target range and velocity estimation scheme by extracting the delay-Doppler information from the RIS-reshaped echo signals. Numerical results demonstrate that the proposed schemes can achieve a <inline-formula><tex-math>$99.7%$</tex-math></inline-formula> target detection rate, a <inline-formula><tex-math>$10^{-3}$</tex-math></inline-formula>-rad level direction estimation accuracy, and a <inline-formula><tex-math>$10^{-6}$</tex-math></inline-formula>-m/<inline-formula><tex-math>$10^{-5}$</tex-math></inline-formula>-m/s level range/velocity estimation accuracy.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"1470-1484"},"PeriodicalIF":4.6,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143640563","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

Optimal TOA-Based Sensor-Anchor-Source Geometries and Estimation Bounds for Simultaneous Sensor and Source Localization 基于toa的最优传感器锚源几何和同时定位的估计界

IF 4.6 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-03-14 DOI: 10.1109/TSP.2025.3545928

Sheng Xu;Bing Zhu;Xinyu Wu;Kutluyıl Doğançay

{"title":"Optimal TOA-Based Sensor-Anchor-Source Geometries and Estimation Bounds for Simultaneous Sensor and Source Localization","authors":"Sheng Xu;Bing Zhu;Xinyu Wu;Kutluyıl Doğançay","doi":"10.1109/TSP.2025.3545928","DOIUrl":"10.1109/TSP.2025.3545928","url":null,"abstract":"This paper focuses on optimal time-of-arrival (TOA) sensor placement for simultaneous sensor and source localization (SSSL) with the help of selected anchors at known positions in the environment. Firstly, the problem of sensor placement for SSSL is analyzed and formulated as an optimization task based on the approximate Cramér-Rao lower bound (CRLB), which is an approximation of the intractable true CRLB. Secondly, by minimizing the trace of the approximate CRLB, the optimal accuracy bounds for the estimated sensor and source positions are derived, which can serve as a useful evaluation metric for other studies. Thirdly, a systematic solution including both the analytical and algebraic methods is proposed to obtain the optimal sensor-anchor-source geometries for achieving the approximate bounds simultaneously. Significantly, the analytical sensor placement approach can quickly offer an optimal placement for some special cases, and the algebraic algorithm can provide a (sub-)optimal solution numerically for the general case. Furthermore, theoretical guidance for placing anchors in the localization area is provided. Finally, the theoretical findings and proposed algorithms are verified by computer simulations and experimental studies, demonstrating that the optimized sensor positions yield accurate performance. The results in this paper can be utilized as an evaluation tool and a performance improvement guidance for practical SSSL problems.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"1727-1743"},"PeriodicalIF":4.6,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143635660","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

Greedy Selection for Heterogeneous Sensors 异构传感器的贪婪选择

IF 4.6 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-03-12 DOI: 10.1109/TSP.2025.3549301

Kaushani Majumder;Sibi Raj B. Pillai;Satish Mulleti

{"title":"Greedy Selection for Heterogeneous Sensors","authors":"Kaushani Majumder;Sibi Raj B. Pillai;Satish Mulleti","doi":"10.1109/TSP.2025.3549301","DOIUrl":"10.1109/TSP.2025.3549301","url":null,"abstract":"Simultaneous operation of all sensors in a large-scale sensor network is power-consuming and computationally expensive. Hence, it is desirable to select fewer sensors. A greedy algorithm is widely used for sensor selection in homogeneous networks with a theoretical worst-case performance of <inline-formula><tex-math>$boldsymbol{(mathbf{1-1}/mathbf{e})mathbf{approx 63}}$</tex-math></inline-formula>% of the optimal performance when optimizing submodular metrics. For heterogeneous sensor networks (HSNs) comprising multiple sets of sensors, most of the existing sensor selection methods optimize the performance constrained by a budget on the total value of the selected sensors. However, in many applications, the number of sensors to select from each set is known apriori and solutions are not well-explored. For this problem, we propose a joint greedy heterogeneous sensor selection algorithm. Theoretically, we show that the worst-case performance of the proposed algorithm is bounded to <inline-formula><tex-math>$50$</tex-math></inline-formula>% of the optimum for submodular cost metrics. In the special case of HSNs with two sensor networks, the performance guarantee can be improved to <inline-formula><tex-math>$63$</tex-math></inline-formula>% when the number of sensors to select from one set is much smaller than the other. To validate our results experimentally, we propose a submodular metric based on the frame potential measure that considers both the correlation among the sensor measurements and their heterogeneity. We prove theoretical bounds for the mean squared error of the solution when this performance metric is used. We validate our results through simulation experiments considering both linear and non-linear measurement models corrupted by additive noise and quantization errors. Our experiments show that the proposed algorithm results in <inline-formula><tex-math>$4 {boldsymbol{mathbf{-}}} 10$</tex-math></inline-formula> dB lower error than existing methods.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"1394-1409"},"PeriodicalIF":4.6,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143608003","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

Arithmetic Average Density Fusion—Part IV: Distributed Heterogeneous Fusion of RFS and LRFS Filters via Variational Approximation 算术平均密度融合-第四部分：通过变分逼近的RFS和LRFS滤波器的分布异质融合

IF 4.6 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-03-11 DOI: 10.1109/TSP.2025.3550157

Tiancheng Li;Haozhe Liang;Guchong Li;Jesús García Herrero;Quan Pan

{"title":"Arithmetic Average Density Fusion—Part IV: Distributed Heterogeneous Fusion of RFS and LRFS Filters via Variational Approximation","authors":"Tiancheng Li;Haozhe Liang;Guchong Li;Jesús García Herrero;Quan Pan","doi":"10.1109/TSP.2025.3550157","DOIUrl":"10.1109/TSP.2025.3550157","url":null,"abstract":"This paper is the fourth part of a series of papers on the arithmetic average (AA) density fusion approach and its application for target tracking. In this paper, we address the intricate challenge of distributed heterogeneous multisensor multitarget tracking, where each inter-connected sensor operates a probability hypothesis density (PHD) filter, a multiple Bernoulli (MB) filter or a labeled MB (LMB) filter and they cooperate with each other via information fusion. Our recent work has proven that the existing linear fusion of these filters is all exactly built on averaging their respective unlabeled/labeled PHDs. Based on this finding, two PHD-AA fusion approaches are proposed via variational minimization of the upper bound of the Kullback-Leibler divergence between the local and multi-filter averaged PHDs subject to cardinality consensus based on the Gaussian mixture implementation, enabling heterogeneous filter cooperation. One focuses solely on fitting the weights of the local Gaussian components (L-GCs), while the other simultaneously fits all the parameters of the L-GCs at each sensor, both seeking average consensus on the unlabeled PHD, irrespective of the specific posterior form of the local filters. For the distributed peer-to-peer communication, both the classic consensus and flooding paradigms have been investigated. Simulations have demonstrated the effectiveness and flexibility of the proposed approaches in both homogeneous and heterogeneous scenarios.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"1454-1469"},"PeriodicalIF":4.6,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143599455","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

Optimal Bilinear Equalizer for Cell-Free Massive MIMO Systems over Correlated Rician Channels 相关信道上无小区大规模MIMO系统的最优双线性均衡器

IF 5.4 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-03-11 DOI: 10.1109/tsp.2025.3547380

Zhe Wang, Jiayi Zhang, Emil Björnson, Dusit Niyato, Bo Ai

引用次数: 0

Online Federated Reproduced Gradient Descent With Time-Varying Global Optima 时变全局最优在线联邦再现梯度下降

IF 4.6 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-03-11 DOI: 10.1109/TSP.2025.3549591

Yifu Lin;Wenling Li;Jia Song;Xiaoming Li

{"title":"Online Federated Reproduced Gradient Descent With Time-Varying Global Optima","authors":"Yifu Lin;Wenling Li;Jia Song;Xiaoming Li","doi":"10.1109/TSP.2025.3549591","DOIUrl":"10.1109/TSP.2025.3549591","url":null,"abstract":"This paper addresses an online federated learning problem, where the time drift in data distribution leads to time-varying global optima. To adapt to the drift, this paper designs a random Fourier features (RFF) model combined with Reproducing Kernel Hilbert Space (RKHS) theory to tracking the global gradient. Meanwhile, the model also can mitigate gradient variance from local data and gradient bias due to data heterogeneity. Based on this model, the paper further proposes an online federated reproduced gradient descent (OFedRGD) algorithm. The Wasserstein distance is then employed as a distribution metric to analyze the regret by OFedRGD, which is composed of cumulative distribution drifts and cumulative gradient error caused by stochasticity and heterogeneity. Additionally, a set of CLEAR-datasets, including two online learning tasks, are used to test the proposed algorithm. The results show that the proposed algorithm can effectively improve classification accuracy in the two tasks by <inline-formula><tex-math>$5%$</tex-math></inline-formula> and <inline-formula><tex-math>$16%$</tex-math></inline-formula>, respectively, and its performance is less adversely affected by the degree of data dispersion.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"1379-1393"},"PeriodicalIF":4.6,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143599456","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

Spatially Scalable Recursive Estimation of Gaussian Process Terrain Maps Using Local Basis Functions 基于局部基函数的高斯过程地形图空间可伸缩递归估计

IF 4.6 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-03-11 DOI: 10.1109/TSP.2025.3549966

Frida Viset;Rudy Helmons;Manon Kok

{"title":"Spatially Scalable Recursive Estimation of Gaussian Process Terrain Maps Using Local Basis Functions","authors":"Frida Viset;Rudy Helmons;Manon Kok","doi":"10.1109/TSP.2025.3549966","DOIUrl":"10.1109/TSP.2025.3549966","url":null,"abstract":"We address the computational challenges of large-scale geospatial mapping with Gaussian process (GP) regression by performing localized computations rather than processing the entire map simultaneously. Traditional approaches to GP regression often involve computational and storage costs that either scale with the number of measurements, or with the spatial extent of the mapped area, limiting their scalability for real-time applications. Our method places a global grid of finite-support basis functions and restricts computations to a local subset of the grid 1) surrounding the measurement when the map is updated, and 2) surrounding the query point when the map is queried. This localized approach ensures that only the relevant area is updated or queried at each timestep, significantly reducing computational complexity while maintaining accuracy. Unlike many existing methods, which suffer from boundary effects or increased computational costs with mapped area, our localized approach avoids discontinuities and ensures that computational costs remain manageable regardless of map size. This approximation to GP mapping provides high accuracy with limited computational budget for the specialized task of performing fast online map updates and fast online queries of large-scale geospatial maps. It is therefore a suitable approximation for use in real-time applications where such properties are desirable, such as real-time simultaneous localization and mapping (SLAM) in large, nonlinear geospatial fields. We show on experimental data with magnetic field measurements that our algorithm is faster and equally accurate compared to existing methods, both for recursive magnetic field mapping and for magnetic field SLAM.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"1444-1453"},"PeriodicalIF":4.6,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143599471","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