Digital Signal Processing最新文献

{"title":"CSI fingerprint positioning method based on PD array in VLP systems with signal blockage","authors":"Kaiyao Wang,&nbsp;Jiacheng Feng,&nbsp;Zhiyong Hong","doi":"10.1016/j.dsp.2025.105374","DOIUrl":"10.1016/j.dsp.2025.105374","url":null,"abstract":"<div><div>In visible light fingerprint positioning, the line of sight (LOS) signal between the photodetector (PD) and the LED may be blocked by randomly moving people or objects, resulting in degradation of positioning accuracy. To solve this problem, this paper studies a fingerprint positioning method based on PD arrays and channel state information (CSI). The proposed method leverages the spatial arrangement of the PD array to constrain multiple CSI fingerprint matching operations, rather than relying on a single PD for fingerprint matching. Two algorithms are proposed: the PD array minimum matching error (PAMME) algorithm and the PD array LOS path selection (PALS) algorithm. The PAMME algorithm leverages the spatial relationship between multiple PDs to perform multi-point matching, calculating cumulative matching errors to mitigate the limitations of single PDs in fingerprint matching. Building on PAMME, the PALS algorithm estimates the LOS signal, selecting signal combinations with the smallest matching error and removing interference from reflection paths, further improving positioning accuracy. To reduce computational complexity in multi-PD fingerprint matching, the particle swarm optimization (PSO) algorithm is integrated into the method. A segmented search strategy with nonlinear variation factors and Gaussian perturbation is introduced to avoid local optima. In a 4 m × 4 m × 3 m indoor multi-path simulation environment, where two LOS signals are randomly blocked, the PAMME and PALS methods achieve average positioning errors of 0.5 cm and 0.21 cm, respectively. This represents error reductions of 64% and 85% compared to single PD-based CSI fingerprint positioning. Additionally, the proposed PSO strategy optimization reduces the time complexity of PAMME by 94% and PALS by 50%, with minimal increases in positioning error. The simulation results demonstrate that the proposed multi-PD fingerprint positioning method achieves excellent positioning performance with a moderate increase in computational complexity. This highlights the method’s potential and advantages, offering new insights and approaches for indoor fingerprint positioning research.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105374"},"PeriodicalIF":2.9,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144231360","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}

{"title":"Attention-Guided Bi-direction Temporal-aware Network for speech-based depression recognition","authors":"Jingyi Liu ,&nbsp;Yuanyuan Shang ,&nbsp;Mengyuan Yang ,&nbsp;Zhuhong Shao ,&nbsp;Hui Ding ,&nbsp;Tie Liu","doi":"10.1016/j.dsp.2025.105359","DOIUrl":"10.1016/j.dsp.2025.105359","url":null,"abstract":"<div><div>Depression is a serious mental illness that affects daily life and has drawn increasing global concern. While speech contains valuable emotional markers for depression recognition, accurate estimation remains challenging. We propose the Attention Guided Bi-direction Temporal-aware Network (AGBiTNet), a novel architecture designed for speech-based depression recognition. AGBiTNet incorporates a Bi-direction Temporal-aware Module (BiTM) to capture bidirectional temporal dependencies and a Frequency-aware Attention Module (FAM) to extract discriminative emotional cues from multi-scale spectral representations. To further enhance regression accuracy and improve feature robustness, a joint loss combining Huber loss and Generalized End-to-End (GE2E) loss is adopted. Extensive experiments on AVEC 2013, 2014, and 2017 datasets demonstrate that AGBiTNet achieves competitive performance with RMSE/MAE values of 9.36/7.21, 9.38/7.24, and 5.29/4.20, respectively. Ablation and statistical analyses confirm the reliability of these results, highlighting the proposed approach as an effective and lightweight solution for speech-based depression assessment with promising practical applicability.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105359"},"PeriodicalIF":2.9,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144203931","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}

{"title":"Hybrid synthesis approach for enhanced sidelobe suppression in linear and planar antenna arrays","authors":"Ahmed M. Elkhawaga ,&nbsp;Mohamed Aboualalaa ,&nbsp;Heba S. Dawood ,&nbsp;Mustafa M. Abd Elnaby","doi":"10.1016/j.dsp.2025.105373","DOIUrl":"10.1016/j.dsp.2025.105373","url":null,"abstract":"<div><div>Side Lobe Level (SLL) suppression is a fundamental challenge in antenna array design, as high sidelobes degrade radiation efficiency and lead to increased interference. While several approaches including Method of Moments (MoM), Genetic Algorithms (GA), and convolution-based synthesis have been explored for SLL reduction, each suffers from specific limitations such as computational intensity, convergence instability, or structural constraints. This paper proposes a novel hybrid synthesis framework termed 1DC/MoM/GA, which integrates the analytical precision of MoM, the global search capability of GA, and the spatial expansion power of one-dimensional convolution (1DC). For planar arrays, a virtual antenna array (VAA) model is employed, and the final excitation matrix is constructed using the Kronecker product of the optimized linear arrays. The approach strategically decomposes the planar arrays into vertical and horizontal linear sub-arrays to reduce the optimization burden, followed by convolution-based enhancement to achieve deep SLL suppression. The proposed method achieves up to a sixfold reduction in SLL while maintaining computational efficiency. Validation is carried out through MATLAB simulations and CST full-wave modeling, with results demonstrating superior performance compared to state-of-the-art techniques.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105373"},"PeriodicalIF":2.9,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144263121","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}

{"title":"GDALaneNet: A feature fusion strategy balances global awareness and detail accuracy in lane detection","authors":"Jiao Hong,&nbsp;Yiling Han,&nbsp;Yi Liu","doi":"10.1016/j.dsp.2025.105360","DOIUrl":"10.1016/j.dsp.2025.105360","url":null,"abstract":"<div><div>Lane detection serves as a core component in autonomous driving technology, forming the foundation for crucial functions such as vehicle autonomous navigation, path planning, and obstacle avoidance. With the continuous advancement of deep neural networks, lane detection algorithm models have seen significant improvements in accuracy, robustness, and real-time performance. However, these models still face challenges posed by the lack of visual cues, such as adverse lighting conditions and occlusion issues. Therefore, to adapt to complex and variable road environments and achieve accurate and efficient lane detection, a new lane detection model named GDALaneNet, which integrates local and global information, has been explored. Through a dual-stream pathway, we combine the ROI features aggregated with global context information with the input features to obtain prior knowledge of lane lines in the image, forming initial proposals and enhancing the model's real-time detection capability. Subsequently, we iteratively refine the proposal features using features from various levels to improve the completeness of the initial proposals, thereby achieving accurate lane detection. Experimental results on three benchmark datasets demonstrate that our method achieves an F1 score of 79.8% on the CULane dataset with a real-time inference speed of over 200 FPS, and an F1 score of 97.93% on the Tusimple dataset, showcasing improvements in both speed and accuracy. On the LLAMAS dataset, F1 score reached 97.1%, the recall rate and accuracy have been effectively improved.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105360"},"PeriodicalIF":2.9,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144254331","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}

{"title":"A novel radar target detection algorithm via enhanced geometric distance matrix for CFAR detector","authors":"Yuxuan Liang,&nbsp;Yibing Li,&nbsp;Jialong Han,&nbsp;Tao Jiang","doi":"10.1016/j.dsp.2025.105358","DOIUrl":"10.1016/j.dsp.2025.105358","url":null,"abstract":"<div><div>This paper introduces a matrix CFAR (Constant False Alarm Rate) detector based on an enhanced geometric distance framework for signal detection. Radar echo signals are modeled as positive definite Toeplitz matrices, forming a matrix manifold, thereby reformulating the detection task as a classification problem within this manifold. Two geometric distances—the Root-Euclidean Distance (RED) and the Cholesky-Euclidean Distance (CED)—are refined into the Enhanced Root-Euclidean Distance (eRED) and the Enhanced Cholesky-Euclidean Distance (eCED), with corresponding detectors developed based on these enhancements. Additionally, the Anisotropy Index and discriminative capability descriptors are derived for RED, CED, eRED, and eCED. The results show that eRED and eCED offer superior discriminative capabilities over the original distances, leading to improved performance of the geometric detectors compared to existing algorithms. Numerical simulations and real-clutter data tests demonstrate that the proposed detectors outperform conventional methods, validating the effectiveness of the approach.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105358"},"PeriodicalIF":2.9,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144170439","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}

{"title":"A unified framework for gamma nonlinearity and asynchronous crosstalk mitigation for optical camera communications","authors":"Zhe Wang ,&nbsp;Liangzhuang Wei ,&nbsp;Songzuo Liu ,&nbsp;Zhigang Shang ,&nbsp;Song Li","doi":"10.1016/j.dsp.2025.105351","DOIUrl":"10.1016/j.dsp.2025.105351","url":null,"abstract":"<div><div>As a cutting-edge of multimedia-based data concealing technique, optical camera communication (OCC) has garnered considerable attention in fundamental platforms for many emerging applications. Typically, OCC employs smart screens or display arrays as transmitters and cameras as receivers. However, one key challenge for super-pixel level OCC is the phenomenon of asynchronous frame recovery and gamma correction, which is pivotal to facilitate seamless optical end-to-end interconnects. Off-the-shelf cameras are susceptible to the combined impact of nonlinear gamma effects and asynchronous inter-frame crosstalk, significantly degrading the video-based steganography. In this paper, we present a novel scheme termed nonlinear gamma correction with inter-frame crosstalk mitigation (NGC-ICM). It consists of the skewness-based gamma correction (SGC) and frame-level constrained independent component analysis (FCICA) module, to jointly post-equalize the nonlinear gamma effect and reception phase misalignment, thereby facilitating flexible multimedia data embedding. Theoretical analysis validates that the proposed NGC-ICM scheme, offers notable advantages such as rapid iterative convergence, low computational complexity, and a broad range of linear and nonlinear parameter compensation capabilities. From a quantitative analysis perspective, the NGC-ICM algorithm achieves a Q factor improvement of approximately 20 dB for the air link at 4.5 meters and 18 dB for the underwater link at 1.5 meters.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105351"},"PeriodicalIF":2.9,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144168187","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}

{"title":"Radar communication integrated signal design and processing methods based on amplitude coded modulation","authors":"Caoyi Jiao ,&nbsp;Xiaobin Liu ,&nbsp;Zhenyu Qiao ,&nbsp;Zhaoyu Gu ,&nbsp;Feng Zhao","doi":"10.1016/j.dsp.2025.105362","DOIUrl":"10.1016/j.dsp.2025.105362","url":null,"abstract":"<div><div>To address the challenges of high bit error rate (BER) and false target peaks in high-resolution range profile (HRRP) within dual-functional radar-communication (DFRC) systems, this study proposes innovative processing methods for linear frequency modulation (LFM) waveform modulated by amplitude codes, alternatively referred to as LFM-ASK waveform. The characteristics of the LFM-ASK waveform are investigated. For communication function, a reference signal is constructed based on the segment summation of the LFM signal, and the amplitude codes are recovered by sampling the reference signal's matched filter output at each code beginning and applying a threshold-based decision. For radar function, a pair of complement codes is employed to generate two LFM-ASK signals. The same order false target peaks in the two HRRPs of the echoes have opposite phases, and the false targets can be effectively eliminated by summing the two HRRPs. Comprehensive simulations and experiments have been conducted, demonstrating the effectiveness of the proposed processing methods. The results indicate that the proposed demodulation method decreases the BER by 36 % and 16 % compared to envelope demodulation and coherent demodulation at 0 dB signal-to-noise ratio (SNR). Additionally, the proposed elimination method not only suppresses signal-induced false targets but also reduces the number of noise-induced false targets from over 3 to 0 compared to the compressive sensing method.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105362"},"PeriodicalIF":2.9,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144212914","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}

{"title":"An end-to-end optimized feature specific data imputation for recurrent neural networks under missing data","authors":"Safa Onur Sahin ,&nbsp;Suleyman Serdar Kozat","doi":"10.1016/j.dsp.2025.105349","DOIUrl":"10.1016/j.dsp.2025.105349","url":null,"abstract":"<div><div>We investigate regression and classification of time series under missing data, which happens in most real-life applications and severely degrades the performance of most, if not all, machine learning algorithms. We introduce a novel missing-valued time series processing algorithm involving a set of different imputation models to complete these missing values. We formulate the imputation selection in a multi-armed bandit framework, where imputation functions are selected specifically for each feature. Particularly, we simultaneously select an imputation model for each feature/component of the input vector among a set of imputation algorithms and train these imputation models along with the network for the target task in an end-to-end manner. Since the individual features may have widely distinct characteristics and temporal behaviors, a single imputation algorithm may show less than adequate performance for the imputation of all of the features. Our method is generic so that the set of imputation models can straightforwardly be extended by the additional imputation methods, and is also equally applicable to recurrent neural network architectures, even when the data arrival times of the feature vectors are non-uniform. In our experiments, we achieved significant performance improvements with respect to the state-of-the-art methods in well-known real-life datasets under different missing data regimes.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105349"},"PeriodicalIF":2.9,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144190036","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}

{"title":"Online radar screening pulse width allocation strategy based on non-stationary bandit","authors":"Hongyu Zhu ,&nbsp;Yefei Wang ,&nbsp;Rong Xie ,&nbsp;Zheng Liu ,&nbsp;Shuwen Xu ,&nbsp;Lei Ran","doi":"10.1016/j.dsp.2025.105363","DOIUrl":"10.1016/j.dsp.2025.105363","url":null,"abstract":"<div><div>With the development of jamming technologies, jammers can respond to radar signals within a short period, causing radar frequency-hopping strategies to fail. In the face of jammers with instantaneous frequency measurements (IFM) capabilities, radio frequency (RF) screening techniques are an effective countermeasure. However, in practice, the jamming strategy is usually unknown to the radar. Moreover, when the jammer's strategy changes, failing to promptly adjust the shielding pulse parameters will result in a significant degradation of the RF screening anti-jamming effectiveness. To overcome the limitations caused by the lack of information about the jammer and the non-stationary environment due to changes in the jammer's IFM time, this paper proposes an online radar screening pulse width allocation method based on a non-stationary multi-armed bandit (MAB). This method combines discounted historical rewards and sliding window rewards, allowing it to better adapt to the non-stationary jamming environment. Simulation results show that the proposed method has a faster convergence speed than the discounted method and a stronger exploration capability than the sliding window method. It can effectively enhance radar performance in countering instantaneous frequency measuring jammers in non-stationary jamming environments.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105363"},"PeriodicalIF":2.9,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144203930","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}

{"title":"Performance evaluation of an IRS-assisted NOMA communication system with two-way relaying","authors":"Ashish,&nbsp;Shubham Anand,&nbsp;Preetam Kumar","doi":"10.1016/j.dsp.2025.105356","DOIUrl":"10.1016/j.dsp.2025.105356","url":null,"abstract":"<div><div>Intelligent Reflecting Surfaces (IRS) have emerged as a key enabling technology for B5G/6G systems which can smartly reconfigure the changing wireless environment. This study addresses key B5G network use cases like massive device connectivity and enhanced urban coverage, ideal for smart cities and large-scale IoT. Integrating an IRS into a non-orthogonal multiple access (NOMA) based two-way relay system reduces outage probability (OP), boosts ergodic capacity (EC), and tackles challenges like spectrum scarcity, energy efficiency, and the growing demand for reliable connectivity in densely populated environments. In this work, a novel NOMA communication system model assisted by a relay and an IRS has been analyzed in both uplink and downlink scenarios. The analytical expression for the outage probability (OP) of the relay-IRS-user link with new channel characteristics and Nakagami-<em>m</em> fading has been derived. This work also presents an analysis of the range of reflective elements required to ensure the minimum quality of service (QoS) for the far user. The system's ergodic capacity (EC) has also been analyzed. Finally, simulation results of outage probability (OP) and ergodic capacity (EC) have been presented. The results demonstrate that incorporating an IRS into the system model significantly improves performance.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105356"},"PeriodicalIF":2.9,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144168186","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}