Signal Processing最新文献_第8页

Combinatorial-restless-bandit-based transmitter–receiver online selection of distributed MIMO radar with non-stationary channels 基于组合-无频带-发射机-接收机在线选择的非稳态信道分布式多输入多输出雷达

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-09-12 DOI: 10.1016/j.sigpro.2024.109707

Yuhang Hao , Zengfu Wang , Jing Fu , Xianglong Bai , Can Li , Quan Pan

{"title":"Combinatorial-restless-bandit-based transmitter–receiver online selection of distributed MIMO radar with non-stationary channels","authors":"Yuhang Hao , Zengfu Wang , Jing Fu , Xianglong Bai , Can Li , Quan Pan","doi":"10.1016/j.sigpro.2024.109707","DOIUrl":"10.1016/j.sigpro.2024.109707","url":null,"abstract":"<div><p>In a distributed multiple-input multiple-output (MIMO) radar for tracking moving targets, optimizing sensible selections of the transmitter–receiver pairs is crucial for maximizing the sum of signal-to-interference-plus-noise ratios (SINRs), as it directly affects the tracking accuracy. In solving the trade-off between exploitation and exploration in non-stationary channels, the optimization problem is modeled by a restless multi-armed bandits model. This paper regards the estimated SINR mean reward as the state of an arm (transceiver channel). The SINR reward of each arm is estimated based on whether it is probed. A closed loop is established between SINR rewards and the dynamic states of targets, which are estimated via the interacting multiple model-unscented Kalman filter. The combinatorial optimized selection of transmitter–receiver pairs at each time is accomplished by using the binary particle swarm optimization with the SINR index fitness function, where the index represents the upper bound on the confidence of the SINR reward. Above all, a multi-group combinatorial-restless-bandit closed-loop (MG-CRB-CL) algorithm is proposed. Simulation results for different scenarios are provided to verify the effectiveness and superior performance of MG-CRB-CL.</p></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"227 ","pages":"Article 109707"},"PeriodicalIF":3.4,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239229","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

Sparse channel estimation for underwater acoustic OFDM systems with super-nested pilot design 采用超嵌套先导设计的水下声波 OFDM 系统的稀疏信道估计

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-09-12 DOI: 10.1016/j.sigpro.2024.109709

Lei Wan , Shuimei Deng , Yougan Chen , En Cheng

{"title":"Sparse channel estimation for underwater acoustic OFDM systems with super-nested pilot design","authors":"Lei Wan , Shuimei Deng , Yougan Chen , En Cheng","doi":"10.1016/j.sigpro.2024.109709","DOIUrl":"10.1016/j.sigpro.2024.109709","url":null,"abstract":"<div><p>Underwater acoustic channels are usually sparse and have large delay spread. In this paper, super-nested array structure in the field of array signal processing is borrowed to be the pilot design of underwater acoustic OFDM systems, in order to better estimate large delay spread channels with limited number of pilots. Specifically, by constructing the pilot subcarriers’ covariance matrix and the pilot position difference, the virtual pilot on the differential co-array are employed for sparse channel estimation. In order to reduce the error between the estimated pilot subcarriers’ covariance matrix and the ideal covariance matrix, the cross-correlation matrix of pilot subcarriers is estimated in advance for interference cancellation. Then the sparse iterative covariance estimation algorithm (SPICE) is adopted to further refine the covariance matrix and improve the channel estimation performance. Simulation, pool and sea experimental results show that the proposed method can effectively estimate the large delay spread sparse channels and improve the performance of underwater acoustic OFDM systems.</p></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"227 ","pages":"Article 109709"},"PeriodicalIF":3.4,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239231","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

Contrast-preserving image smoothing via the truncated first-order rational function 通过截断一阶有理函数平滑对比度保护图像

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-09-12 DOI: 10.1016/j.sigpro.2024.109700

Jiaqi Mei , Xiaoguang Lv , Biao Fang , Le Jiang

引用次数: 0

Guaranteed matrix recovery using weighted nuclear norm plus weighted total variation minimization 使用加权核规范加权总变异最小化保证矩阵恢复

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-09-11 DOI: 10.1016/j.sigpro.2024.109706

Xinling Liu , Jiangjun Peng , Jingyao Hou , Yao Wang , Jianjun Wang

{"title":"Guaranteed matrix recovery using weighted nuclear norm plus weighted total variation minimization","authors":"Xinling Liu , Jiangjun Peng , Jingyao Hou , Yao Wang , Jianjun Wang","doi":"10.1016/j.sigpro.2024.109706","DOIUrl":"10.1016/j.sigpro.2024.109706","url":null,"abstract":"<div><p>This work presents a general framework regarding the recovery of matrices equipped with hybrid low-rank and local-smooth properties from just a few measurements consisting of linear combinations of the matrix entries. Concretely, we consider the problem of robust low-rank matrix recovery using Weighted Nuclear Norm plus Weight Total Variation (WNNWTV) minimization. First of all, based on a new restricted isometry property, we prove that the WNNWTV method possesses an error bound consisting of a low-rank approximation term, a total variation approximation term, and an observation error term. It should be noted that although there are many models considering both properties, there are very few recoverable error theories about such models. Specifically, the theoretical error bound provides an automatic mechanism to reducing regularization parameters with no need for cross-validation while keeping almost the same selection result with commonly used cross-validation technique. Subsequently, the proposed method is reformulated into a regularized unconstrained problem, and we study its optimization aspects in detail based on the Alternating Direction Method of Multipliers (ADMM). Extensive experiments on synthetic data and two applications, i.e. hyperspectral image recovery and dynamic magnetic resonance imaging recovery verified our theories and proposed algorithms.</p></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"227 ","pages":"Article 109706"},"PeriodicalIF":3.4,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239228","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

Lightweight image super-resolution with sliding Proxy Attention Network 利用滑动代理注意力网络实现轻量级图像超分辨率

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-09-11 DOI: 10.1016/j.sigpro.2024.109704

Zhenyu Hu, Wanjie Sun, Zhenzhong Chen

{"title":"Lightweight image super-resolution with sliding Proxy Attention Network","authors":"Zhenyu Hu, Wanjie Sun, Zhenzhong Chen","doi":"10.1016/j.sigpro.2024.109704","DOIUrl":"10.1016/j.sigpro.2024.109704","url":null,"abstract":"<div><p>Recently, image super-resolution (SR) models using window-based Transformers have demonstrated superior performance compared to SR models based on convolutional neural networks. Nevertheless, Transformer-based SR models often entail high computational demands. This is due to the adoption of shifted window self-attention following the window self-attention layer to model long-range relationships, resulting in additional computational overhead. Moreover, extracting local image features only with the self-attention mechanism is insufficient to reconstruct rich high-frequency image content. To overcome these challenges, we propose the Sliding Proxy Attention Network (SPAN), capable of recovering high-quality High-Resolution (HR) images from Low-Resolution (LR) inputs with substantially fewer model parameters and computational operations. The primary innovation of SPAN lies in the Sliding Proxy Transformer Block (SPTB), integrating the local detail sensitivity of convolution with the long-range dependency modeling of self-attention mechanism. Key components within SPTB include the Enhanced Local Feature Extraction Block (ELFEB) and the Sliding Proxy Attention Block (SPAB). ELFEB is designed to enhance the local receptive field with lightweight parameters for high-frequency details compensation. SPAB optimizes computational efficiency by implementing intra-window and cross-window attention in a single operation through leveraging window overlap. Experimental results demonstrate that SPAN can produce high-quality SR images while effectively managing computational complexity. The code is publicly available at: <span><span>https://github.com/zononhzy/SPAN</span><svg><path></path></svg></span>.</p></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"227 ","pages":"Article 109704"},"PeriodicalIF":3.4,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142171659","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 fast Lanczos-based hierarchical algorithm for tensor ring decomposition 基于 Lanczos 的张量环分解分层快速算法

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-09-11 DOI: 10.1016/j.sigpro.2024.109705

Cheng-Wei Sun , Ting-Zhu Huang , Hong-Xia Dou , Ting Xu , Liang-Jian Deng

{"title":"A fast Lanczos-based hierarchical algorithm for tensor ring decomposition","authors":"Cheng-Wei Sun , Ting-Zhu Huang , Hong-Xia Dou , Ting Xu , Liang-Jian Deng","doi":"10.1016/j.sigpro.2024.109705","DOIUrl":"10.1016/j.sigpro.2024.109705","url":null,"abstract":"<div><p>Tensor ring (TR) decomposition has made remarkable achievements in numerous high-order data processing tasks. However, the current alternating least squares (ALS)- and singular value decomposition (SVD)-based algorithms for TR decomposition, i.e., TR-ALS and TR-SVD, especially the former, are computationally expensive, making them unfriendly for large-scale data processing. This paper adopts three strategies to propose a novel fast TR decomposition algorithm: (1) Use a more efficient Lanczos bidiagonalization algorithm than SVD to generate the TR core tensors. (2) Exploit the hierarchical strategy to generate the TR core tensors in parallel. (3) Employ new reshaping and unfolding operations to reduce the dimensionality of the data used to generate TR core tensors. By incorporating these three strategies, we propose the TR-HLanczos algorithm for fast TR decomposition. This algorithm seamlessly produces the TR core tensors through the Lanczos bidiagonalization algorithm in a hierarchical manner. The effectiveness of the proposed TR-HLanczos algorithm is demonstrated through experimental results on both highly oscillatory functions and real-world datasets. For instance, when dealing with data of size <span><math><mrow><mn>5</mn><msup><mrow><mn>0</mn></mrow><mrow><mn>5</mn></mrow></msup></mrow></math></span>, TR-HLanczos is nearly 561 times and 18 times faster than algorithms based on ALS and SVD, respectively.</p></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"227 ","pages":"Article 109705"},"PeriodicalIF":3.4,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239293","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

Designing sparse extended nested arrays with high degrees of freedom and low coupling 设计具有高自由度和低耦合度的稀疏扩展嵌套阵列

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-09-10 DOI: 10.1016/j.sigpro.2024.109702

Shun He , Nan Sun , Zhiwei Yang

引用次数: 0

Iterative UKF under generalized maximum correntropy criterion for intermittent observation systems with complex non-Gaussian noise 具有复杂非高斯噪声的间歇观测系统的广义最大熵准则下的迭代 UKF

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-09-07 DOI: 10.1016/j.sigpro.2024.109701

Min Zhang , Xinmin Song , Wei Xing Zheng , Zheng Liu

{"title":"Iterative UKF under generalized maximum correntropy criterion for intermittent observation systems with complex non-Gaussian noise","authors":"Min Zhang , Xinmin Song , Wei Xing Zheng , Zheng Liu","doi":"10.1016/j.sigpro.2024.109701","DOIUrl":"10.1016/j.sigpro.2024.109701","url":null,"abstract":"<div><p>The traditional unscented Kalman filters (UKFs) under the maximum correntropy criterion provide a powerful tool for nonlinear state estimation with heavy-tailed non-Gaussian noise. Nevertheless, the above-mentioned filters may yield biased estimates because the Gaussian kernel function can only handle certain types of non-Gaussian noise. Additionally, the use of statistical linearization methods can result in approximation errors when solving linear observation equations, while the system may also experience observation data loss. Therefore, a new iterative UKF with intermittent observations under the generalized maximum correntropy criterion is proposed for systems with complex non-Gaussian noise, called GMCC-IO-IUKF. Firstly, the connection between the UKF with and without intermittent observations is established by designing a coefficient matrix including intermittent observation variables, so as to derive the UKF with intermittent observations under the maximum correntropy criterion. Secondly, for the measurement update of GMCC-IO-IUKF, a nonlinear regression augmented model that can deal with both prediction and observation errors is established using the coefficient matrix and the nonlinear function. To better adapt to different types of non-Gaussian noise, the generalized Gaussian kernel function is substituted for the traditional Gaussian kernel function. Theoretically, GMCC-IO-IUKF can achieve better estimation performance by directly employing the nonlinear function and the latest iteration value. Finally, a classical target tracking model is used to evaluate the estimation performance and feasibility of our proposed GMCC-IO-IUKF algorithm. It appears from the experiment results that our proposed GMCC-IO-IUKF can not only promote estimation precision but also handle complex non-Gaussian noise flexibly.</p></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"227 ","pages":"Article 109701"},"PeriodicalIF":3.4,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142168574","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 characterization of reflective surfaces using dual-polarization GNSS-R 利用双极化 GNSS-R 确定反射表面的特征

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-09-07 DOI: 10.1016/j.sigpro.2024.109692

Daniele Oliveira Silva , Lucas Santos Pereira , Edson Rodrigo Schlosser , Marcos V.T. Heckler , Felix Antreich

{"title":"On the characterization of reflective surfaces using dual-polarization GNSS-R","authors":"Daniele Oliveira Silva , Lucas Santos Pereira , Edson Rodrigo Schlosser , Marcos V.T. Heckler , Felix Antreich","doi":"10.1016/j.sigpro.2024.109692","DOIUrl":"10.1016/j.sigpro.2024.109692","url":null,"abstract":"<div><p>Global navigation satellite systems reflectometry (GNSS-R) is a technique to extract information from reflecting surfaces by the reflected GNSS signals. GNSS-R has garnered increasing attention in the scientific literature due to its continuous global coverage and its superior spatial resolution. Moreover, operating in the L-band renders GNSS-R relatively immune to adverse weather conditions and affords high sensitivity to soil electrical properties. This work introduces a new approach with a dual-polarization antenna, left-hand circular polarized (LHCP) and right-hand circular polarized (RHCP), receiving the reflected signal from a sufficiently smooth surface so that all reflected energy arrives from the specular reflection point. The objective is to characterize the reflecting surface by extracting the relative permittivity and conductivity from the reflected signal. In contrast to other studies found in the literature, the reflection of the GNSS signal on different materials, including dielectric and conductive materials is considered. We derive a maximum likelihood estimator (MLE) for estimating the dielectric parameters of the reflective surface and other parameters of the reflected signal. We also derive the respective Cramer–Rao Lower Bound (CRLB) evaluating the performance of the MLE. The attained results are assessed based on the signal-to-noise ratio (SNR) and the angle of reflection of the reflected signal, which are the parameters that predominantly influence the proposed approach. Lower elevation angles, for instance, lead to higher estimation accuracy, while for reflective surfaces composed of metallic materials a higher SNR is needed to yield favorable estimation performance. Regarding dielectric materials, the estimation results are encouraging and thus enable diverse remote sensing applications by GNSS-R using the proposed setup.</p></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"227 ","pages":"Article 109692"},"PeriodicalIF":3.4,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142229556","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

RMANet: Refined-mixed attention network for progressive low-light image enhancement RMANet：用于渐进式低照度图像增强的精制混合注意力网络

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-09-06 DOI: 10.1016/j.sigpro.2024.109689

Ke Chen , Kaibing Zhang , Feifei Pang , Xinbo Gao , Guang Shi

{"title":"RMANet: Refined-mixed attention network for progressive low-light image enhancement","authors":"Ke Chen , Kaibing Zhang , Feifei Pang , Xinbo Gao , Guang Shi","doi":"10.1016/j.sigpro.2024.109689","DOIUrl":"10.1016/j.sigpro.2024.109689","url":null,"abstract":"<div><p>Multi-scale feature fusion has been recognized as an effective strategy to boost the quality of low-light images. However, most existing methods directly extract multi-scale contextual information from severely degraded and down-sampled low-light images, resulting in a large amount of unexpected noise and degradation contaminating the learned multi-scale features. Moreover, there exist large redundant and overlapping features when directly concatenating multi-scale feature maps, which fails to consider different contributions of different scales. To conquer the above challenges, this paper presents a novel approach termed progressive Refined-Mixed Attention Network (RMANet) for low-light image enhancement. The proposed RMANet first targets a single-scale pre-enhancement and then progressively increases multi-scale spatial-channel attention fusion in a coarse-to-fine fashion. Additionally, we elaborately devise a Refined-Mixed Attention Module (RMAM) to first learn a parallel spatial-channel dominant features and then selectively integrate dominant features in the spatial and channel dimensions across multiple scales. Noticeably, our proposed RMANet is a lightweight yet flexible end-to-end framework that adapts to diverse application scenarios. Thorough experiments carried out upon three popular benchmark databases demonstrate that our approach surpasses existing methods in terms of both quantitative quality metrics and visual quality assessment. The code will be available at <span><span>https://github.com/kbzhang0505/RMANet</span><svg><path></path></svg></span>.</p></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"227 ","pages":"Article 109689"},"PeriodicalIF":3.4,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142164118","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