Signal Processing最新文献

{"title":"A state-of-the-art review on acoustic preservation of historical worship spaces through auralization","authors":"Hannes Rosseel,&nbsp;Toon van Waterschoot","doi":"10.1016/j.sigpro.2025.109992","DOIUrl":"10.1016/j.sigpro.2025.109992","url":null,"abstract":"<div><div>Historical Worship Spaces (HWS) are significant architectural landmarks which hold both cultural and spiritual value. The acoustic properties of these spaces play a crucial role in historical and contemporary religious liturgies, rituals, and ceremonies, as well as in the performance of sacred music. However, the original acoustic characteristics of these spaces are often at risk due to repurposing, renovations, natural disasters, or deterioration over time. This paper presents a comprehensive review of the current state of research on the acquisition, analysis, and synthesis of acoustics, with a focus on HWS. An example case study of the Nassau chapel in Brussels, Belgium, is presented to demonstrate the application of these techniques for the preservation and auralization of historical worship space acoustics. The paper concludes with a discussion of the challenges and opportunities in the field, and outlines future research directions.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"234 ","pages":"Article 109992"},"PeriodicalIF":3.4,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pulse processing — Overview and challenges","authors":"Jonathan H. Manton","doi":"10.1016/j.sigpro.2025.109978","DOIUrl":"10.1016/j.sigpro.2025.109978","url":null,"abstract":"<div><div>The detection of irregularly spaced pulses of non-negligible width is a fascinating yet under-explored topic in signal processing. It sits adjacent to other core topics such as radar and symbol detection yet has its own distinctive challenges. Even modern techniques such as compressed sensing perform worse than may be expected on pulse processing problems. Real-world applications include nuclear spectroscopy, flow cytometry, seismic signal processing and neural spike sorting, and these in turn have applications to environmental radiation monitoring, surveying, diagnostic medicine, industrial imaging, biomedical imaging, top-down proteomics, and security screening, to name just a few. This overview paper endeavours to position the pulse processing problem in the context of signal processing. It also describes some current challenges in the field.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"234 ","pages":"Article 109978"},"PeriodicalIF":3.4,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Frequency offset deception velocity-based method for discriminating between physical targets and active false targets","authors":"Deyu Li,&nbsp;Siyi Yao,&nbsp;Yi Liao,&nbsp;Jian Yan,&nbsp;Yusheng Fu","doi":"10.1016/j.sigpro.2025.109977","DOIUrl":"10.1016/j.sigpro.2025.109977","url":null,"abstract":"<div><div>The discrimination of false targets by multistatic radar utilizing data-level fusion is contingent upon the differences in spatial information observed by receivers of different orientations. Nevertheless, if the target is situated in the far field, the jamming discrimination performance of multistatic radar is limited by the baseline distance of the receivers. To address this challenge, this paper designs a multistatic frequency diversity radar to mislead the carrier frequency estimation of the target jammer. This scheme introduces a difference in spectral information to the spatial information of the multistatic radar, thereby enhancing the jamming discrimination performance. In light of the above, we propose a frequency offset deception velocity-based (FODVB) method to discriminate active false targets. The method effectively fuses the spatial and frequency information to discriminate the false targets accurately and applies to multi-target scenarios. Furthermore, an optimal frequency selection strategy based on target orientation information is proposed to achieve the optimal discrimination performance of the FODVB method. The effectiveness of the proposed method is validated through Monte Carlo simulations.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"234 ","pages":"Article 109977"},"PeriodicalIF":3.4,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143628569","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}

{"title":"Low interactive direct position determination of radio emitters with hybrid measurements","authors":"Ming-Yi You ,&nbsp;Lin Gao ,&nbsp;Yun-Xia Ye ,&nbsp;Wei Wang","doi":"10.1016/j.sigpro.2025.109987","DOIUrl":"10.1016/j.sigpro.2025.109987","url":null,"abstract":"<div><div>This paper proposes a direct position determination (DPD) method for stationary and moving non-cooperative sources. Employing an unbalanced group of measurements consisting of uncompressed measurements at the central receiver and compressed measurements from all other auxiliary receivers, the method estimates the source position directly in the hybrid measurement domain without original signal recovering, where the compressing matrix is not restricted to any specific form. A block coordinate descent (BCD)-like iterative algorithm is proposed to handle the high-dimensional optimization problem of joint position and velocity estimation for moving emitters, where a generalized cross ambiguity function (GCAF) is proposed to extract the time-differences-of-arrival (TDOA) parameters from the hybrid measurements to initialize the iteration process. In addition, the hybrid measurements-based Cramér–Rao lower bound (CRLB) for emitter position is derived for performance evaluation. Several numerical case studies are carried out to evaluate the effectiveness of the proposed DPD method as well as the proposed GCAF. The proposed method is expected to extend the applicability of compressive sensing (CS)-based DPD to cases where there is relative radial motion between the source.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"234 ","pages":"Article 109987"},"PeriodicalIF":3.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621478","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}

{"title":"TOA estimation via cross-correlation-based atomic norm minimization","authors":"Shuang Wei ,&nbsp;Zhichao Niu ,&nbsp;Di He ,&nbsp;Jiawei Lei","doi":"10.1016/j.sigpro.2025.109989","DOIUrl":"10.1016/j.sigpro.2025.109989","url":null,"abstract":"<div><div>This paper proposes a novel Cross-Correlation-based Atomic Norm Minimization method (CC-ANM) to estimate Time-of-Arrival (TOA) parameters with enhanced accuracy. It leverages a gridless approach based on atomic norm to address the cross-correlation model, which is effective in mitigating the impact of non-independently and identically distributed (non-i.i.d.) Gaussian noise. A new optimization framework is formulated to tackle this challenge, and its dual problem expressed through a Semi-Definite Programming (SDP) is derived. By utilizing the characteristics of dual problem, the proposed method can estimate TOA parameters without the need for prior information of the path count under high Signal-to-Noise Ratio (SNR) conditions. To overcome the constraints imposed by traditional root polynomials in low SNR scenarios, the proposed method develops a derivative-based root-finding algorithm to extract TOA parameters from the dual polynomial. It can not only significantly reduce the estimation errors introduced by the discretization process, but also address the performance limitations under low SNR conditions. Simulation results demonstrate that the proposed CC-ANM method closely approximates the Cramer–Rao Lower Bound (CRLB) and outperforms existing methods across a range of SNR levels and path configurations.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"234 ","pages":"Article 109989"},"PeriodicalIF":3.4,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601445","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}

{"title":"High-accuracy image steganography with invertible neural network and generative adversarial network","authors":"Ke Wang,&nbsp;Yani Zhu,&nbsp;Qi Chang,&nbsp;Junyu Wang,&nbsp;Ye Yao","doi":"10.1016/j.sigpro.2025.109988","DOIUrl":"10.1016/j.sigpro.2025.109988","url":null,"abstract":"<div><div>Image steganography conceals secret messages imperceptibly within cover images. However, many existing deep learning-based image steganography methods have limitations in visual quality, payload size, and security. Specifically, they often require error correction codes for complete message extraction. In this paper, we propose a novel image steganography network architecture based on Invertible Neural Network (INN) and Generative Adversarial Network (GAN). Leveraging the reversibility of INN and the connection with the hidden network, we design three extraction networks based on DenseNet, shared weights, and unshared weights. These are respectively combined with the hidden network and discriminator network to create new network structures, effectively improving invisibility and message extraction accuracy. Furthermore, the discriminator participates in adversarial training by comparing cover and stego images in a patch-to-patch manner, thereby enhancing visual quality and security. Extensive experiments demonstrate the effectiveness of our proposed method across various aspects, including image quality, payload, extraction accuracy, and security, particularly achieving close to 100% message extraction accuracy without requiring error correction codes.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"234 ","pages":"Article 109988"},"PeriodicalIF":3.4,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601402","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}

{"title":"Understanding encoder–decoder structures in machine learning using information measures","authors":"Jorge F. Silva ,&nbsp;Victor Faraggi ,&nbsp;Camilo Ramirez ,&nbsp;Alvaro Egaña ,&nbsp;Eduardo Pavez","doi":"10.1016/j.sigpro.2025.109983","DOIUrl":"10.1016/j.sigpro.2025.109983","url":null,"abstract":"<div><div>We present a theory of representation learning to model and understand the role of encoder–decoder design in machine learning (ML) from an information-theoretic angle. We use two main information concepts, information sufficiency (IS) and mutual information loss to represent predictive structures in machine learning. Our first main result provides a functional expression that characterizes the class of probabilistic models consistent with an IS encoder–decoder latent predictive structure. This result formally justifies the encoder–decoder forward stages many modern ML architectures adopt to learn latent (compressed) representations for classification. To illustrate IS as a realistic and relevant model assumption, we revisit some known ML concepts and present some interesting new examples: invariant, robust, sparse, and digital models. Furthermore, our IS characterization allows us to tackle the fundamental question of how much performance could be lost, using the cross entropy risk, when a given encoder–decoder architecture is adopted in a learning setting. Here, our second main result shows that a mutual information loss quantifies the lack of expressiveness attributed to the choice of a (biased) encoder–decoder ML design. Finally, we address the problem of universal cross-entropy learning with an encoder–decoder design where necessary and sufficiency conditions are established to meet this requirement. In all these results, Shannon’s information measures offer new interpretations and explanations for representation learning.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"234 ","pages":"Article 109983"},"PeriodicalIF":3.4,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621480","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}

{"title":"A language-guided cross-modal semantic fusion retrieval method","authors":"Ligu Zhu ,&nbsp;Fei Zhou ,&nbsp;Suping Wang ,&nbsp;Lei Shi ,&nbsp;Feifei Kou ,&nbsp;Zeyu Li ,&nbsp;Pengpeng Zhou","doi":"10.1016/j.sigpro.2025.109993","DOIUrl":"10.1016/j.sigpro.2025.109993","url":null,"abstract":"<div><div>The rapid growth of the Internet and big data has led to the generation of large-scale multimodal data, presenting challenges for traditional retrieval methods. These methods often rely on a two-stage architecture involving retrieval and reranking, which struggles with integrating the semantic differences between visual and textual modalities. This limitation hampers the fusion of information and reduces the accuracy and efficiency of cross-modal retrieval. To overcome these challenges, we propose FusionRM, a language-guided cross-modal semantic fusion retrieval method. FusionRM utilizes the expressive power of textual semantics to bridge the knowledge gap between visual and linguistic modalities. By combining implicit visual knowledge with explicit textual knowledge, FusionRM creates a unified embedding space, aligning semantics across modalities and improving retrieval accuracy and efficiency of multimodal information processing. Experiments on the multi-hop, multimodal WebQA dataset show that FusionRM outperforms traditional methods across multiple metrics, demonstrating superior performance and generalization in open-domain retrieval.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"234 ","pages":"Article 109993"},"PeriodicalIF":3.4,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621479","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}

{"title":"Enhanced channel estimation for double RIS-aided MIMO systems using coupled tensor decompositions","authors":"Gerald C. Nwalozie ,&nbsp;André L.F. de Almeida ,&nbsp;Martin Haardt","doi":"10.1016/j.sigpro.2025.109979","DOIUrl":"10.1016/j.sigpro.2025.109979","url":null,"abstract":"<div><div>In this paper, we consider a double-RIS (D-RIS)-aided flat-fading MIMO system and propose an interference-free channel training and estimation protocol, where the two single-reflection links and the one double-reflection link are estimated separately. Specifically, by using the proposed training protocol, the signal measurements of a particular reflection link can be extracted interference-free from the measurements of the superposition of the three links. We show that some channels are associated with two different components of the received signal.Exploiting the common channels involved in the single and double reflection links while recasting the received signals as tensors, we formulate the coupled tensor-based least square Khatri–Rao factorization (C-KRAFT) algorithm which is a closed-form solution and an enhanced iterative solution with less restrictions on the identifiability constraints, the coupled-alternating least square (C-ALS) algorithm. The C-KRAFT and C-ALS based channel estimation schemes are used to obtain the channel matrices in both single and double reflection links.We show that the proposed coupled tensor decomposition-based channel estimation schemes offer more accurate channel estimates under less restrictive identifiability constraints compared to competing channel estimation methods. Simulation results are provided showing the effectiveness of the proposedalgorithms.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"234 ","pages":"Article 109979"},"PeriodicalIF":3.4,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel adaptive direct signal interference cancellation method for underwater active electromagnetic detection systems using an error signal power-based variable step-size Fast Block Least Mean Square algorithm","authors":"Yan Ma,&nbsp;Hao Zhang,&nbsp;Ke Yang","doi":"10.1016/j.sigpro.2025.109957","DOIUrl":"10.1016/j.sigpro.2025.109957","url":null,"abstract":"<div><div>As a promising candidate to detect the underwater targets, the underwater active electromagnetic detection system has gained more attention in the field of marine exploration. Because of the separation of the transmitting and receiving antennas, the direct signal interference in the receiving end would be a great challenge during the operation, which severely deteriorates the system’s capability of target identification and localization. This paper proposes a novel direct signal interference cancellation method based on an error signal power-driven variable step-size fast block Least Mean Square (PVSS-FBLMS) algorithm to address the direct signal interference cancellation issue in the underwater active EM detection system. The proposed algorithm aligns well with the system’s characteristic of block-wise data transmission and demonstrates lower complexity, especially for higher FIR filter orders, compared to the Least Mean Square and Normalized Least Mean Square algorithms. Considering the limited time available for direct signal interference cancellation, the proposed algorithm introduces a variable step-size adjustment criterion based on the error signal power to accelerate convergence, while ensuring the robustness of the algorithm. The simulation has been conducted, which demonstrates that the proposed algorithm converges approximate 46.8% faster than that of the improved variable step-size least mean square (IVSS-LMS) and variable step-size least mean square (VSS-LMS) algorithms while its computational complexity is only about 40% that of the two algorithms when the FIR filter order is 128. The direct signal interference cancellation performance of the proposed algorithm is significantly better than that of the IVSS-LMS and VSS-LMS algorithms at low DSI-to-noise ratios under the simulation condition. Additionally, the simulation results show that the proposed algorithm performs steadily in a highly abrupt change of the noise and the DSI’s amplitude. Besides, the in-field experiments are conducted to validate the effectiveness of the proposed algorithm. The experimental results show that the convergence rate of the proposed algorithm is notably faster than that of the IVSS-LMS and VSS-LMS algorithms, with a steady-state output variance on the order of <span><math><mrow><mn>1</mn><msup><mrow><mn>0</mn></mrow><mrow><mo>−</mo><mn>6</mn></mrow></msup><msup><mrow><mi>V</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></math></span>.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"234 ","pages":"Article 109957"},"PeriodicalIF":3.4,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143591982","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}