Signal Processing最新文献

Recursive estimators and hybrid Cramér–Rao bounds for discrete-time Markovian dynamic systems 离散马尔可夫动态系统的递归估计量和混合cram<s:1> - rao界

IF 3.6 2区工程技术

Signal Processing Pub Date : 2025-09-30 DOI: 10.1016/j.sigpro.2025.110284

Sara El Bouch , Samy Labsir , Jérôme Galy , Jordi Vilà-Valls , Eric Chaumette

{"title":"Recursive estimators and hybrid Cramér–Rao bounds for discrete-time Markovian dynamic systems","authors":"Sara El Bouch , Samy Labsir , Jérôme Galy , Jordi Vilà-Valls , Eric Chaumette","doi":"10.1016/j.sigpro.2025.110284","DOIUrl":"10.1016/j.sigpro.2025.110284","url":null,"abstract":"<div><div>This article addresses the joint estimation of random states and deterministic parameters within a wide class of linear discrete state-space (DSS) models when a large set of dependent observations is available. Two models are considered, depending on whether the initial state is assumed to be deterministic or random: the generalized conditional signal model and the generalized unconditional signal model. A unified recursive method for estimating the initial state, current state, and unknown deterministic parameters, is obtained by resorting to the Kalman Filter (KF), then generalized to the class of nonlinear DSS models compatible with the extended KF. Hence, to assess the efficiency of these estimators, we also derive recursive hybrid Cramér–Rao bounds for Markovian dynamic systems. A unified framework is established for bounds on complex-valued initial and current states in the presence of unknown deterministic parameters. Finally, the article includes numerical simulations of the empirical mean squared error of the proposed estimators, provides closed-form expressions of the bounds, and demonstrates their practical relevance through two radar application examples.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"239 ","pages":"Article 110284"},"PeriodicalIF":3.6,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145219937","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 deep learning-based maneuvering target tracking with temporal convolutional networks 基于深度学习的机动目标时域卷积跟踪

IF 3.6 2区工程技术

Signal Processing Pub Date : 2025-09-29 DOI: 10.1016/j.sigpro.2025.110322

Lei Xia , Shurui Zhang , Yuhang Hu , Renli Zhang , Song Li , Weixing Sheng

引用次数: 0

BUStega: A generalized coverless image steganography framework based on diffusion models and U2-Net BUStega：一种基于扩散模型和u2net的广义无覆盖图像隐写框架

IF 3.6 2区工程技术

Signal Processing Pub Date : 2025-09-26 DOI: 10.1016/j.sigpro.2025.110317

Shengcai Zhang, Junkai Fu, Dezhi An

{"title":"BUStega: A generalized coverless image steganography framework based on diffusion models and U2-Net","authors":"Shengcai Zhang, Junkai Fu, Dezhi An","doi":"10.1016/j.sigpro.2025.110317","DOIUrl":"10.1016/j.sigpro.2025.110317","url":null,"abstract":"<div><div>Image steganography has evolved along two major paradigms: traditional methods that embed secret images into cover images, and the emerging Coverless Image Steganography (CIS), which eliminates the need for carriers by directly embedding data through image features, significantly enhancing concealment. Recent CIS approaches driven by diffusion models have gained attention but face three critical challenges: (1) dependence on private prompts, which, if leaked, compromise security; (2) frequent key exchanges during transmission, increasing the risk of leakage; and (3) limited generative fidelity, leading to loss of detail in reconstructed images. To address these issues, a novel training-free CIS framework, BUStega, is proposed, combining diffusion models with U<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span>-Net. A semantic private key is generated through optimized BLIP visual encoding and semantic distillation, improving both uniqueness and robustness. U<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span>-Net is employed to generate adaptive embedding masks based on visual saliency, enabling more precise information placement. The integration of diffusion-based modulation and mask-guided control enhances robustness against compression and noise attacks. Comprehensive evaluations on the Stega260 benchmark demonstrate that the proposed method outperforms existing techniques in terms of security, robustness, steganographic quality, and reconstruction fidelity, highlighting its strong potential for generalized CIS applications.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"239 ","pages":"Article 110317"},"PeriodicalIF":3.6,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145220013","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

Spectrally compatible barrage jamming signal synthesis under moment constraints 矩约束下的频谱兼容弹幕干扰信号合成

IF 3.6 2区工程技术

Signal Processing Pub Date : 2025-09-26 DOI: 10.1016/j.sigpro.2025.110303

Yongjun Chen , Da Li , Bo Tang

引用次数: 0

Low-light image enhancement method based on joint guiding total variation 基于联合引导全变分的微光图像增强方法

IF 3.6 2区工程技术

Signal Processing Pub Date : 2025-09-26 DOI: 10.1016/j.sigpro.2025.110316

Chaoyang Chen , Pan Hu , Lei He , Ling Wang

{"title":"Low-light image enhancement method based on joint guiding total variation","authors":"Chaoyang Chen , Pan Hu , Lei He , Ling Wang","doi":"10.1016/j.sigpro.2025.110316","DOIUrl":"10.1016/j.sigpro.2025.110316","url":null,"abstract":"<div><div>Low-light image enhancement is crucial for high-quality image display and various visual applications. However, maintaining the visual naturalness of an image while enhancing its brightness presents a challenging task. We propose a novel algorithm for low-light image enhancement that joint guiding total variation and luminance adaptive correction. In order to obtain illuminated images with clear structure and smooth detail texture, the total variation of the window incorporating the guiding filter is used as the illumination regularity term. Logarithmic mean local variance is used as a reflection regularization term to extract texture details better reflecting the image. In addition, to address the issue of color distortion in areas with extremely low illumination, an arc-tangent transform is used to enhance the color and contrast in the very low-light region. We solve the model using an alternating optimization algorithm. In the model, each sub-problem is transformed into a vectorized least squares regression, with closed-form solutions. Experimental results on several public datasets demonstrate that our method suppresses the noise well while maintaining the color contrast and detail information. In comparison to other advanced algorithms, the proposed model delivers superior results in both subjective and objective evaluations.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"239 ","pages":"Article 110316"},"PeriodicalIF":3.6,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157559","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 radar with chirp diversity for achieving ultra-low range sidelobe level and enhancing range resolution 具有啁啾分集的FDA雷达，可实现超低距离旁瓣电平，提高距离分辨率

IF 3.6 2区工程技术

Signal Processing Pub Date : 2025-09-26 DOI: 10.1016/j.sigpro.2025.110314

Ben Zhang, Yongsheng Zhang, Feng He, Lei Yu, Yi Su

{"title":"FDA radar with chirp diversity for achieving ultra-low range sidelobe level and enhancing range resolution","authors":"Ben Zhang, Yongsheng Zhang, Feng He, Lei Yu, Yi Su","doi":"10.1016/j.sigpro.2025.110314","DOIUrl":"10.1016/j.sigpro.2025.110314","url":null,"abstract":"<div><div>The composite beam scanning characteristics of coherent frequency diverse array (FDA) radar induces a decline in range resolution, which is restored by increasing the beam dwell time through the Barker codes. However, this approach can lead to a rise in the range sidelobe level (RSL) and a loss of spatial interference suppression capability. For FDA radar, common methods of reducing the RSL can lead to a loss in signal-to-noise ratio (SNR), while methods of enhancing range resolution can result in a decrease in interference suppression capability and Doppler tolerance. In this paper, we investigate a novel transmission diversity technique, namely element-to-element chirp diversity, to reduce RSL and enhance range resolution. The proposed approach is predicated on shaping the power spectrum of the aggregated transmit signal, making it approximate the local Gaussian power spectrum and the power spectrum of the baseband waveform, respectively. The method’s underlying mathematical principles are thoroughly analyzed, and the favorable properties of the optimized waveform have been evaluated using the ambiguity function. Extensive numerical and instance results demonstrate a significant reduction in the RSL and an enhancement in range resolution. Specifically, our approach circumvents any loss in processing SNR and substantial degradation in spatial interference suppression capability.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"239 ","pages":"Article 110314"},"PeriodicalIF":3.6,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145219938","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

Robust M-estimation-based algorithm with generalized minimum error entropy criterion for active noise control 基于广义最小误差熵准则的稳健m估计主动噪声控制算法

IF 3.6 2区工程技术

Signal Processing Pub Date : 2025-09-26 DOI: 10.1016/j.sigpro.2025.110320

Bingyan Zhang, Xiaomei Chen

{"title":"Robust M-estimation-based algorithm with generalized minimum error entropy criterion for active noise control","authors":"Bingyan Zhang, Xiaomei Chen","doi":"10.1016/j.sigpro.2025.110320","DOIUrl":"10.1016/j.sigpro.2025.110320","url":null,"abstract":"<div><div>As a prominent approach within the framework of information theoretic learning (ITL), the concept of error entropy has demonstrated significant efficacy in active noise control (ANC). However, the Gaussian kernel function used in error entropy has a fixed structure that lacks dynamic adaptability, limiting the performance of the filtered-x minimum error entropy (FxMEE) algorithm in dealing with diverse noise characteristics. To address this issue, an adaptive filtered-x generalized minimum error entropy (FxGMEE) algorithm is proposed, which employs a flexible-shape generalized Gaussian density function as its kernel. Furthermore, the filtered-x generalized minimum error entropy (MF-FxGMEE) algorithm based on the M-estimation Fair function is developed as a robust variant, aiming to mitigate the adverse effects of non-Gaussian disturbances. By incorporating M-estimation theory, the MF-FxGMEE algorithm effectively identifies and suppresses outliers via a smooth weighting mechanism, enhancing system stability in non-Gaussian noise environments. We also analyze the theoretical properties of the MF-FxGMEE algorithm, including its mean error behavior, mean square convergence, and computational complexity. Simulation studies are performed to validate the proposed algorithms, demonstrating superior convergence performance over existing methods.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"239 ","pages":"Article 110320"},"PeriodicalIF":3.6,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145220011","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

Indirect Kalman filtering for robust GNSS spoofing detection in signal quality monitoring 信号质量监测中GNSS欺骗检测的间接卡尔曼滤波

IF 3.6 2区工程技术

Signal Processing Pub Date : 2025-09-25 DOI: 10.1016/j.sigpro.2025.110321

Xiaoqin Jin , Xiaoyu Zhang , Shuaiyong Zheng

{"title":"Indirect Kalman filtering for robust GNSS spoofing detection in signal quality monitoring","authors":"Xiaoqin Jin , Xiaoyu Zhang , Shuaiyong Zheng","doi":"10.1016/j.sigpro.2025.110321","DOIUrl":"10.1016/j.sigpro.2025.110321","url":null,"abstract":"<div><div>Malicious spoofing poses a significant threat to the integrity of global navigation satellite system (GNSS), compromising the reliability and accuracy of measurements essential for navigation, positioning, and timing applications. Signal quality monitoring (SQM) metrics are crucial for detecting spoofing attacks by providing real-time assessments of GNSS signal integrity. However, noise interference in these metrics can degrade detection performance, leading to delayed alarms and reduced security. This paper introduces an innovative indirect Kalman filtering (IKF) approach to enhance spoofing detection by effectively mitigating the impact of noise on SQM metrics. The proposed method employs Kalman filtering to independently smooth metrics derived from the in-phase and quadrature channel outputs of multi-correlators. The non-coherent accumulation of the Kalman filter’s output state variables forms a comprehensive detection metric, while the steady-state noise variance of the Kalman filter’s output is utilized to compute the detection threshold. Theoretical analysis and experimental validation demonstrate that the IKF significantly outperforms traditional mean filtering methods in terms of detection accuracy and alarm latency. Experimental results indicate that the IKF achieves an average detection rate exceeding 80 % and reduces alarm times by approximately 20 s. This work provides a robust framework for real-time GNSS signal integrity monitoring and offers an effective solution for enhancing GNSS security against spoofing threats.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"239 ","pages":"Article 110321"},"PeriodicalIF":3.6,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145219936","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

Cramér–Rao bound analysis of nested arrays under impulsive noise with coarrays and FLOSs 脉冲噪声下嵌套阵列与阵列和FLOSs的cram<s:1> - rao界分析

IF 3.6 2区工程技术

Signal Processing Pub Date : 2025-09-25 DOI: 10.1016/j.sigpro.2025.110313

Xudong Dong , Jun Zhao , Meng Sun , Xiaofei Zhang , Yide Wang

{"title":"Cramér–Rao bound analysis of nested arrays under impulsive noise with coarrays and FLOSs","authors":"Xudong Dong , Jun Zhao , Meng Sun , Xiaofei Zhang , Yide Wang","doi":"10.1016/j.sigpro.2025.110313","DOIUrl":"10.1016/j.sigpro.2025.110313","url":null,"abstract":"<div><div>Nested arrays are extensively employed in array signal processing to augment the degrees of freedom and enhance estimation precision, and the Cramér–Rao Bound (CRB) for nested arrays in a Gaussian noise environment has been established. Nevertheless, in a practical wireless communication environment, noise usually exhibits an impulsive characteristic. The impulsive noise applied in a uniform linear array (ULA) has been extensively studied in the literature, but only closed-form expressions of CRB with Cauchy and Gaussian noise distributions are given. Although nested arrays have garnered significant attention recently, research on the CRB under impulsive noise conditions remains scarce. In this paper, we provide the CRB expression for direction of arrival (DOA) estimation with nested arrays in an impulsive noise environment, which indicates that the CRB is formulated in terms of the fractional low-order statistics (FLOSs) of received data. Moreover, we also calculate the CRB results for different FLOSs as well as various sparse arrays and validate that the derived CRB makes an important contribution to the performance analysis of sparse arrays in impulsive noise.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"239 ","pages":"Article 110313"},"PeriodicalIF":3.6,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157389","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

Persymmetric adaptive detectors design in the presence of deterministic subspace interference 确定性子空间干扰下的超对称自适应检测器设计

IF 3.6 2区工程技术

Signal Processing Pub Date : 2025-09-25 DOI: 10.1016/j.sigpro.2025.110311

Peiqin Tang , Yuanyuan Jiang , Jinfang Wen , Can Huang , Weijian Liu , Jun Liu

引用次数: 0