Signal Processing最新文献_第9页

Transfer function-based robust filtering: Review and critical evaluation 基于传递函数的鲁棒滤波：回顾与关键评价

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-05-05 DOI: 10.1016/j.sigpro.2025.110060

Oscar G. Ibarra-Manzano, José A. Andrade-Lucio, Miguel A. Vázquez-Olguín, Yuriy S. Shmaliy

{"title":"Transfer function-based robust filtering: Review and critical evaluation","authors":"Oscar G. Ibarra-Manzano, José A. Andrade-Lucio, Miguel A. Vázquez-Olguín, Yuriy S. Shmaliy","doi":"10.1016/j.sigpro.2025.110060","DOIUrl":"10.1016/j.sigpro.2025.110060","url":null,"abstract":"<div><div>Promoted by Wilson in his 1989 year work through the convolution and Hankel operator norms, the transfer function approach (TFA) developed by many authors has earlier emerged as a novel trend of sorts in robust estimation of system state to minimize the estimation error bounded norm for the maximized error bounded norm. This paper takes a fresh look at the problem through the bias correction gain <span><math><mi>K</mi></math></span> of a recursive filter, reviews and revisits the existing robust <span><math><msub><mrow><mi>H</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span>, energy-to-energy or <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span>, energy-to-peak or generalized <span><math><msub><mrow><mi>H</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> (G<span><math><msub><mrow><mi>H</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span>), and peak-to-peak or <span><math><msub><mrow><mi>L</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span> filtering solutions, and critically evaluates their performances. It is shown that the effective <span><math><mi>K</mi></math></span> ranges between the larger gain of the optimal Kalman and the smaller gain of the robust unbiased finite impulse response (UFIR) filter. That is, regardless of the robust criterion, the gain produced by the sophisticated TFA turns out to be quite sandwiched by the Kalman and UFIR filters. The filters are tested based on extensive numerical simulations and experimentally in terms of mean square error, robustness, and quality factor.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"237 ","pages":"Article 110060"},"PeriodicalIF":3.4,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143921910","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

Adaptive robust MIMO radar target localization via capped Frobenius norm 基于上限Frobenius范数的自适应鲁棒MIMO雷达目标定位

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-05-02 DOI: 10.1016/j.sigpro.2025.110069

Jun-Ru Yang , Zhang-Lei Shi , Xiao-Peng Li , Wenxin Xiong , Yaru Fu , Xijun Liang

{"title":"Adaptive robust MIMO radar target localization via capped Frobenius norm","authors":"Jun-Ru Yang , Zhang-Lei Shi , Xiao-Peng Li , Wenxin Xiong , Yaru Fu , Xijun Liang","doi":"10.1016/j.sigpro.2025.110069","DOIUrl":"10.1016/j.sigpro.2025.110069","url":null,"abstract":"<div><div>Most of the existing algorithms for multiple-input multiple-output radar target localization assume that the bistatic range measurements are contaminated by one certain kind of noise only, such as Gaussian noise and impulsive noise. However, when the practical noise violates the original assumed distribution, their localization performance degrades severely. Therefore, adaptive and robust localization algorithms that can achieve good localization performance under both Gaussian and impulsive noise are highly desirable. In this paper, we exploit the truncated least squares loss function called capped Frobenius norm (CFN) to resist outliers. An adaptive update scheme is developed to automatically determine the upper bound of CFN using the normalized median absolute deviation. Then, the nonconvex and nonsmooth CFN-based formulation is transformed into a regularized <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span>-norm optimization problem based on the half-quadratic theory. The alternating optimization (AO) algorithm is adopted as the solver, and closed-form solutions for both subproblems are derived. We also show that the sequence of objective function value generated by the devised algorithm converges. Experimental results verify the superiority of the proposed algorithm over several existing algorithms in terms of localization accuracy under impulsive noise. Furthermore, the devised algorithm can attain comparable performance to <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span>-norm based methods without tweaking hyperparameters under Gaussian noise.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"237 ","pages":"Article 110069"},"PeriodicalIF":3.4,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143917347","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

Joint state estimation and topology inference for graphical dynamical systems 图形动力系统的联合状态估计与拓扑推理

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-04-30 DOI: 10.1016/j.sigpro.2025.110070

Pengfei Fang , Wenling Li , Jia Song , Xiaoming Li , Li Ma

{"title":"Joint state estimation and topology inference for graphical dynamical systems","authors":"Pengfei Fang , Wenling Li , Jia Song , Xiaoming Li , Li Ma","doi":"10.1016/j.sigpro.2025.110070","DOIUrl":"10.1016/j.sigpro.2025.110070","url":null,"abstract":"<div><div>In this paper, we consider the problem of joint state estimation and topology inference for a class of graphical dynamical systems, where the graph topology matrix is involved in the dynamical systems. A non-convex objective function, containing an equality constraint on the row sum of the topology matrix, is established with respect to the state and the topology, in which the estimated node states and observations at the historical time steps are used to infer the graph topology, and a regularization term is designed to enhance the sparsity of the graph topology. Then, the state estimation and topology inference are obtained by solving two convex subproblems in manner of using the Kalman filtering and the alternating direction method of multipliers (ADMM) algorithms, respectively. Specially, by separating the non-differentiable regularization term and utilizing a proximity operator, we derive an iterative solution with high computational efficiency to infer the graph topology in the ADMM algorithm. To verify the effectiveness of the proposed algorithm, simulation with a car-following model is carried out.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"237 ","pages":"Article 110070"},"PeriodicalIF":3.4,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143906414","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

Separable and high-capacity reversible data hiding for encrypted 3D mesh models based on dual multi-MSB predictions 基于双重多msb预测的加密三维网格模型的可分离和大容量可逆数据隐藏

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-04-29 DOI: 10.1016/j.sigpro.2025.110079

Jiacheng Ge , Yingqiang Qiu , Zhisheng Chen , Kaimeng Chen , Xiaodan Lin , Yufeng Dai

{"title":"Separable and high-capacity reversible data hiding for encrypted 3D mesh models based on dual multi-MSB predictions","authors":"Jiacheng Ge , Yingqiang Qiu , Zhisheng Chen , Kaimeng Chen , Xiaodan Lin , Yufeng Dai","doi":"10.1016/j.sigpro.2025.110079","DOIUrl":"10.1016/j.sigpro.2025.110079","url":null,"abstract":"<div><div>Three-dimensional (3D) models, essential for building virtual worlds, are encountering growing challenges in privacy and copyright protection as their usage increases. Reversible data hiding (RDH) in encrypted 3D mesh models not only protects the privacy of the original models through encryption but also embeds additional data for covert communication or access control. This paper proposes a high-capacity, separable RDH method for encrypted 3D models. The approach utilizes integer mapping and incorporates an enhanced dual multiple most significant bit (multi-MSB) prediction strategy to maximize embedding capacity. First, each vertex coordinate is scaled to a decimal value within a predefined range. These values are then encoded into binary digits using integer mapping, with the number of digits determined by a compression threshold. Subsequently, all vertices are processed to identify redundant data that served as embedding room using a multi-MSB self-prediction algorithm, significantly increasing the embedding capacity. Next, after disregarding the redundancy in the MSBs of each vertex, the vertices are classified into an embeddable set and a reference set. The embeddable vertices are then further processed to create additional embedding room through secondary multi-MSB prediction. The auxiliary data, compressed using arithmetic coding, is embedded into the multi-MSB of each encrypted vertex, resulting in encrypted vertices that contain both the auxiliary data and available embedding room. Using the auxiliary data, encrypted additional data is embedded into the reserved embedding room within the multi-MSB of each vertex through bit substitution. Finally, the embedded data can be extracted without errors, and the original 3D mesh can be recovered losslessly. The experimental results demonstrate that the proposed method is highly effective, achieving superior embedding capacity compared to several state-of-the-art methods.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"237 ","pages":"Article 110079"},"PeriodicalIF":3.4,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143906413","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

Transceiver beamforming design of RIS-aided active array radar in cluttered environments 杂波环境下ris辅助有源阵雷达收发波束形成设计

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-04-28 DOI: 10.1016/j.sigpro.2025.110059

Qi Feng, Shengyao Chen, Longyao Ran, Feng Xi, Hongtao Li, Sirui Tian, Zhong Liu

{"title":"Transceiver beamforming design of RIS-aided active array radar in cluttered environments","authors":"Qi Feng, Shengyao Chen, Longyao Ran, Feng Xi, Hongtao Li, Sirui Tian, Zhong Liu","doi":"10.1016/j.sigpro.2025.110059","DOIUrl":"10.1016/j.sigpro.2025.110059","url":null,"abstract":"<div><div>This paper equips a reconfigurable intelligent surface (RIS) to assist the active array radar for boosting its interference suppression ability and enhancing the beamforming gain towards target direction simultaneously. The output signal-to-interference-plus-noise ratio (SINR) is chosen as the metric to jointly design the transmit and receive beamformers of radar array and RIS reflection coefficients. In light of SINR performance and implementation complexity, two operation modes using identical or distinct RIS reflection coefficients in transmit and receive stages (ITR or DTR) are investigated. In each mode, the proposed joint design is formulated into a nonconvex constrained fractional programming problem and the solving algorithm is customized under the block coordinate descent framework. Specifically, the RIS reflection coefficients are respectively optimized by the quartic Riemannian Newton method (RNM) in ITR mode and by the quadratic RNM in DTR mode after Dinkelbach transform. Moreover, a simplified scheme under DTR mode is also given to speed up processing, where the beamforming of radar array and RIS separately concentrates on the beamforming gain enhancement and interference suppression in transmit and receive stages. Numerical results display that both ITR and DTR modes significantly outperform the array radars using an RIS only in receive or transmit stage.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"237 ","pages":"Article 110059"},"PeriodicalIF":3.4,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143892105","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

An interpretable convolutional neural network via generalized time–frequency scattering 基于广义时频散射的可解释卷积神经网络

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-04-28 DOI: 10.1016/j.sigpro.2025.110043

Xiaoping Liu , Gong Chen , Jun Shi , Ran Tao

{"title":"An interpretable convolutional neural network via generalized time–frequency scattering","authors":"Xiaoping Liu , Gong Chen , Jun Shi , Ran Tao","doi":"10.1016/j.sigpro.2025.110043","DOIUrl":"10.1016/j.sigpro.2025.110043","url":null,"abstract":"<div><div>Convolutional neural networks (CNNs) have recently demonstrated impressive performance in complex machine learning tasks. However, the CNN requires a large quantity of annotated data to converge to a good solution, and the theoretical understanding of this network is still in its infancy. Towards this end, a variant of the CNN, dubbed the deep scattering network (DSN), has been proposed by employing the linear time–frequency transform. The DSN inherits the hierarchical structure of the CNN, but chooses predefined wavelet/Gabor filters as its convolutional kernels instead of data-driven linear filters. Unfortunately, the DSN suffers from a major drawback that it is suitable for stationary image textures but not for non-stationary image textures, since wavelet/Gabor filters are intrinsically linear translation-invariant filters. The aim of this paper is to overcome this deficiency based upon a generalized linear time–frequency transform–the short-time fractional Fourier transform (STFRFT) which can be interpreted as a bank of linear translation-variant filters and thus may be well suitable for non-stationary texture analysis. We first introduce a generalized time–frequency scattering transform using the STFRFT. By applying the derived result, we propose an interpretable CNN by cascading the STFRFTs and modulus operators. Moreover, several basic properties of the proposed interpretable CNN are derived, and an efficient implementation of this network is also presented. Finally, the applications of the derived results are discussed.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"237 ","pages":"Article 110043"},"PeriodicalIF":3.4,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896059","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

Unrolled expectation maximization algorithm for radio interferometric imaging in presence of non Gaussian interferences 非高斯干扰下无线电干涉成像的展开期望最大化算法

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-04-28 DOI: 10.1016/j.sigpro.2025.110035

Nawel Arab , Yassine Mhiri , Isabelle Vin , Mohammed Nabil El Korso , Pascal Larzabal

引用次数: 0

Variational resampling-free cubature Kalman filter for GNSS/INS with measurement outlier detection 测量离群点检测GNSS/INS的无重采样变分培养卡尔曼滤波

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-04-27 DOI: 10.1016/j.sigpro.2025.110036

Bingbo Cui , Wu Chen , Duojie Weng , Jingxian Wang , Xinhua Wei , Yongyun Zhu

{"title":"Variational resampling-free cubature Kalman filter for GNSS/INS with measurement outlier detection","authors":"Bingbo Cui , Wu Chen , Duojie Weng , Jingxian Wang , Xinhua Wei , Yongyun Zhu","doi":"10.1016/j.sigpro.2025.110036","DOIUrl":"10.1016/j.sigpro.2025.110036","url":null,"abstract":"<div><div>In the information fusion of GNSS/INS, the cubature Kalman filter (CKF) has been widely recognized for its ability to map the probability distributions more accurately than the extended Kalman filter. The resampling-free sigma-point update framework (SUF) propagates additional information based on the residuals of instantiated points from nonlinear transforms, which approximates the covariance of the posterior state more effectively than resampling-based SUF. Unfortunately, resampling-free SUF inherits the limitations of the KF framework, where measurement outliers caused by GNSS signal blocking and disturbances significantly degrade its performance. In this paper, a variational-based SUF is proposed for GNSS/INS information fusion, in which the measurement noise covariance and outlier indicator are iteratively updated using variational Bayesian inference. Consequently, an adaptive SUF is proposed based on outlier-dependent switching SUFs, leading to the development of a variational resampling-free CKF. Numerical simulations and a car-mounted GNSS/INS field test were conducted to demonstrate the effectiveness of the proposed algorithm. The results indicate that the proposed algorithm can efficiently address measurement outliers and time-varying measurement noise.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"237 ","pages":"Article 110036"},"PeriodicalIF":3.4,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888134","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

Frequency–phase coupled parameter estimation for vibration measurement with LFMCW radar LFMCW雷达振动测量的频相耦合参数估计

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-04-26 DOI: 10.1016/j.sigpro.2025.110033

Xuyao Yu , Zijun Gong , Zhilu Lai

{"title":"Frequency–phase coupled parameter estimation for vibration measurement with LFMCW radar","authors":"Xuyao Yu , Zijun Gong , Zhilu Lai","doi":"10.1016/j.sigpro.2025.110033","DOIUrl":"10.1016/j.sigpro.2025.110033","url":null,"abstract":"<div><div>Linear frequency modulated continuous wave (LFMCW) radar is widely employed in vibration measurement. In the received intermediate frequency signal, the distance information is embedded in both the frequency and phase, i.e., frequency–phase coupling. Early studies rely primarily on classical phase unwrapping algorithms, which frequently fail during rapid or large-amplitude vibrations. Although recent advances have enhanced robustness by incorporating frequency-derived coarse distance estimates as side information for phase unwrapping, these sequential approaches still under-utilize the inherent frequency–phase coupling relationship. In this article, we propose a novel method that jointly leverages both frequency and phase information for direct distance estimation. To start with, we derive a simplified discrete-time baseband signal model, which clearly unveils the coupling. The maximum likelihood (ML) estimation is used to reap the promised performance, but its complexity grows exponentially with the number of observations. To address the complexity barrier, we propose a heuristic method to sequentially solve such a joint optimization problem, and the performance is close to the Cramér–Rao lower bound (CRLB). We analyze the behavior of the ML estimators and discuss the impact of various parameters on system performance. A real-world experiment validates the system model and the proposed algorithm, with results aligning with theoretical analysis.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"237 ","pages":"Article 110033"},"PeriodicalIF":3.4,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143903453","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 inference with incompleteness for logistic regression model 逻辑回归模型的不完备性鲁棒推理

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-04-25 DOI: 10.1016/j.sigpro.2025.110027

M. Cherifi , M.N. El Korso , S. Fortunati , A. Mesloub , L. Ferro-Famil

引用次数: 0