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Complex Video Completion Fusing Low-RankBackground and Deep Foreground Priors

IEEE signal processing LETTERS 2022年 29卷 2737-2741页

作者： Wang, Jian-Li Huang, Ting-Zhu Zhao, Xi-Le Miao, Yu-Chun Univ Elect Sci & Technol China Sch Math Sci Chengdu 611731 Peoples R China Wuhan Univ Sch Comp Sci Wuhan 430072 Peoples R China

Recently, low-rank prior (LRP) has achieved success in tensor completion, thanks to its ability in capturing global correlations. However, since the presence of dynamic foreground breaks the low-rank assumption, LRP sometimes fails to work for complex videos. How to effectively capture the implicit low-rankness is a tricky challenge in complex video completion. To address this challenge, we propose a video completion model, which organically combines the respective merits of deterministic LRP and deep image prior. Specifically, we first decompose a complex video into the dynamic foreground and static background, and then characterize each component individually. For the dynamic foreground, instead of the hand-crafted prior, we consider the deep foreground prior expressed by U-Net architecture in an unsupervised manner, while we consider the tensor low-rank prior for the static background. Moreover, we develop an efficient alternating direction method of multipliers algorithm under the plug-and-play framework to tackle the resulting model. Different from the classic plug-and-play framework with a pre-trained and fixed network, our algorithm can adaptively update the parameters of network during iterations, which enables the network to have a more flexible expression ability. Experimental results verify that the proposed method can do better than some state-of-the-art tensor completion methods in complex video completion.

关键词： Adaptation models Tensors Correlation Heuristic algorithms signal processing algorithms Video surveillance Reliability Complex video completion deep foreground prior low-rank background prior plug-and-play

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Joint Sensor Selection, Beamforming and Phase Control in Reconfigurable Intelligent Surface Aided IoT Fusion Networks

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IEEE WIRELESS COMMUNICATIONS LETTERS 2022年第2期11卷 401-405页

作者： Zhou, Yuyan Liu, Yang Li, Ming Wu, Qingqing Wang, Hao Dalian Univ Technol Sch Informat & Commun Engn Dalian 116024 Peoples R China Univ Macau Dept Elect & Comp Engn Macau Peoples R China ShanghaiTech Univ Sch Informat Sci & Technol Shanghai 201210 Peoples R China

In this letter, we investigate the power minimization problem in an Internet of Things (IoT) sensor network assisted by reconfigurable intelligent surface (RIS). Different from the existing literature, we consider both transmit and non-transmit energy consumption, which leads to a joint sensor selection, beamforming design and RIS phase configuration problem. Based on the cutting-the-edge majorization minimization (MM) and penalty duality decomposition (PDD) frameworks, we develop two solutions which can achieve nearly identical performance as that of exhaustive search method. Extensive numerical results verify the great benefit in power saving via sensor selection and the deployment of RIS device.

关键词： Internet of Things Power demand Array signal processing signal to noise ratio Minimization Surface waves signal processing algorithms Reconfigurable intelligent surface (RIS) group-sparsity IoT sensor network

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Maximum Likelihood Algorithm for Time-Delay Based Multistatic Target Localization

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IEEE signal processing LETTERS 2022年 29卷 847-851页

作者： Panwar, Kuntal Babu, Prabhu Stoica, Petre Indian Inst Technol Ctr Appl Res Elect Delhi 110016 India Uppsala Univ Dept Informat Technol S-75105 Uppsala Sweden

In this letter we address the problem of multistatic target localization using time-delay measurements corrupted by noise with unknown non-uniform variances. More concretely, we consider the problem of joint maximum likelihood (ML) estimation of the target position and the noise variances, for which we propose a majorization-minimization based algorithm. The proposed approach is compared with state-of-the-art algorithms, and the simulation results show the excellent accuracy of our algorithm.

关键词： Location awareness signal processing algorithms Receivers Noise measurement Maximum likelihood estimation Transmitters signal to noise ratio Target localization time-delay measurements maximum-likelihood estimation majorization-minimization

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Beamspace Phase Solving Algorithm for Elevation Angle Estimation

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IEEE signal processing LETTERS 2022年 29卷 742-746页

作者： Chen, Sheng Zhao, Yongbo Hu, Yili Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Shaanxi Peoples R China

This letter discusses the elevation angle estimation problem for a scene containing a direct and a reflected signal. Beamspace processing is an excellent candidate to reduce the computational burden of elevation angle estimation without affecting the multipath phase that contains the reflection coefficient phase and the phase difference between the direct and the reflected signals. In addition, the multipath phase is a function of the target elevation angle. With these considerations, we solve the multipath phase problem without searching within 3D beamspace data and therefore obtain the target elevation angle with a very low computational burden. Under the same prior information, the proposed algorithm manages an estimation accuracy similar to the ones requiring a search under the condition of a certain signal-to-noise ratio. Our evaluation results demonstrate the suitability of the proposed algorithm for engineering applications.

关键词： signal processing algorithms Maximum likelihood estimation Reflection coefficient Mathematical models signal to noise ratio Reflection Phase estimation Elevation angle estimation beamspace processing multipath environment search free

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Diffusion Particle Filtering on the Special Orthogonal Group Using Lie Algebra Statistics

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IEEE signal processing LETTERS 2022年 29卷 2058-2062页

作者： Bordin, Claudio J., Jr. de Figueredo, Caio G. Bruno, Marcelo G. S. Fed Univ ABC BR-09210580 Santo Andre SP Brazil Fed Inst Ceara Boa Viagem BR-63870000 Boa Viagem Brazil Aeronaut Inst Technol BR-12228900 Sao Jose Dos Campos Brazil

In this letter, we introduce new distributed diffusion algorithms to track a sequence of hidden random matrices that evolve on the special orthogonal group. The algorithms are based on the Adapt-then-Combine and the Random Exchange methods, and diffuse Gaussian approximations of posterior densities computed in the Lie algebra of the special orthogonal group. Simulation results show that, in scenarios with nonlinear observation functions, the proposed algorithms perform closely to the centralized particle filter estimator and can outperform competing Extended Kalman Filters.

关键词： Particle filters Estimation Symmetric matrices signal processing algorithms Manifolds Algebra Filtering Statistics on manifolds matrix lie groups diffusion method particle filters

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AVO Analysis Combined With TeagerKaiser Energy Methods for Hydrocarbon Detection

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IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 2022年 19卷 1页

作者： Jiang, Xudong Cao, Junxing Yang, Jinhai Liu, Jie Zhou, Peng Chengdu Univ Technol Minist Educ Key Lab Earth Explorat & Informat Technol Chengdu 610059 Peoples R China Chengdu Univ Technol State Key Lab Oil & Gas Reservoir Geol & Exploita Chengdu 610059 Peoples R China CNOOC Energy Technol & Serv Co Res Inst Zhanjiang Branch Zhanjiang 524000 Peoples R China

An improved amplitude variation with offset (AVO) attribute analysis method combined with the Teagerx2013;Kaiser energy methods for hydrocarbon detection is proposed in this letter. It has a stronger ability to reveal the subtle amplitude anomaly changes caused by hydrocarbons than the traditional AVO analysis method. The Teagerx2013;Kaiser energy operator (TKEO) algorithm is used for enhancing the hydrocarbonsx2019;characteristics of the prestack gathers. The cross Teagerx2013;Kaiser energy operator (CTKEO) is further employed to efficiently highlight the AVO feature of the gathers by calculating the energy interaction between the first trace and the other traces. Finally, the intercept and gradient product (PG) parameters are obtained through AVO analysis for hydrocarbon detection. The model test and the field data applications show that the proposed method can effectively target the gas reservoirs. This letter presents a complementary approach to current AVO analysis methods.

关键词： Hydrocarbons Mathematical model Oils signal processing algorithms Sensitivity Reservoirs Prediction algorithms Amplitude variation with offset (AVO) cross Teager-Kaiser energy operator (CTKEO) hydrocarbon detection Teager-Kaiser energy operator (TKEO)

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Energy Efficient Beamforming Optimization for Integrated Sensing and Communication

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IEEE WIRELESS COMMUNICATIONS LETTERS 2022年第7期11卷 1374-1378页

作者： He, Zhenyao Xu, Wei Shen, Hong Huang, Yongming Xiao, Huahua Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Peoples R China Purple Mt Labs Nanjing 211111 Peoples R China ZTE Corp State Key Lab Mobile Network & Mobile Multimedia Shenzhen 518055 Peoples R China

This letter investigates the optimization of beamforming design in a system with integrated sensing and communication (ISAC), where the base station (BS) sends signals for simultaneous multiuser communication and radar sensing. We aim at maximizing the energy efficiency (EE) of the multiuser communication while guaranteeing the sensing requirement in terms of individual radar beampattern gains. The problem is a complicated nonconvex fractional program which is challenging to be solved. By appropriately reformulating the problem and then applying the techniques of successive convex approximation (SCA) and semidefinite relaxation (SDR), we propose an iterative algorithm to address this problem. In theory, we prove that the introduced relaxation of the SDR is rigorously tight. Numerical results validate the effectiveness of the proposed algorithm.

关键词： Sensors Radar signal to noise ratio Array signal processing Interference Optimization signal processing algorithms Integrated sensing and communication (ISAC) energy efficiency (EE) beamforming optimization

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Computationally-Efficient Overdetermined Blind Source Separation Based on Iterative Source Steering

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IEEE signal processing LETTERS 2022年 29卷 927-931页

作者： Du, Yicheng Scheibler, Robin Togami, Masahito Yoshii, Kazuyoshi Kawahara, Tatsuya Kyoto Univ Grad Sch Informat Kyoto 6068501 Japan LINE Corp Tokyo 1600004 Japan

This paper describesa computationally-efficient optimization algorithm for the blind source separation (BSS) of overdetermined mixtures. In the determined case, a matrix-inversion-free iterative source steering (ISS) algorithm has been proposed for estimating a square demixing matrix as a computationally-efficient alternative to the popular iterative projection (IP) algorithm. The IP algorithm is based on source-wise (i.e., row-wise) updates of the demixing matrix, and lends itself naturally to an extension to overdetermined independent vector analysis (IVA) called OverIVA. In contrast, the ISS algorithm changes the whole demixing matrix at every update, making its extension to the overdetermined case non-trivial. In this paper, we propose a modified ISS algorithm for OverIVA fully exploiting the computational savings of ISS. We also derive an overdetermined extension of independent low-rank matrix analysis (OverILRMA) with the modified ISS algorithm. Experimental results showed that the proposed ISS-based OverIVA and OverILRMA were comparable or superior to the conventional IP-based counterparts in speech separation performance while achieving lower computational cost.

关键词： signal processing algorithms IP networks Iterative algorithms Blind source separation Parameter estimation Microphones Cost function Overdetermined blind source separation independent vector analysis fast algorithm

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Fast and Accurate Spectrum Estimation via Virtual Coarray Interpolation Based on Truncated Nuclear Norm Regularization

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IEEE signal processing LETTERS 2022年 29卷 169-173页

作者： Fan, Qing Liu, Yu Yang, Tao Peng, Hao Univ Elect Sci & Technol China Sch Elect Sci & Engn Chengdu 611731 Peoples R China

Compared with the Nyquist sampling scheme, the coprime sampling scheme reduces the requirement of sampling rate significantly and simultaneously shows high degrees of freedom. Actually, the information received by the sampler is not fully utilized due to the non-uniformity of derived second-order virtual coarray. In addition, the virtual signals corresponding to the non-uniform virtual coarray may be contaminated by noise, which could affect the accuracy of spectrum estimation. In this letter, we propose a novel virtual coarray interpolation method for the inexact Toeplitz covariance matrix based on truncated nuclear norm regularization. The missing elements and exact covariance matrix can be obtained simultaneously by solving the covariance matrix completion problem that contains the error term and non-Toeplitz errors propagation control term. Simulation results demonstrate the superiorities of the proposed spectrum estimation method in terms of accuracy and computational complexity.

关键词： Covariance matrices Interpolation Spectral analysis Estimation Direction-of-arrival estimation Simulation signal processing algorithms Virtual coarray interpolation spectrum estimation coprime sampling truncated nuclear norm

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Steady-State Performance Analysis of the Distributed FxLMS Algorithm for Narrowband ANC System With Frequency Mismatch

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IEEE signal processing LETTERS 2022年 29卷 1167-1171页

作者： Chen, Jing Wu, Ming Gong, Chen Wang, Xiaolin Yang, Jun Chinese Acad Sci Inst Acoust Key Lab Noise & Vibrat Res Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

Distributed narrowband active noise control (NANC) systems using diffusion filtered-x least mean square (FxLMS) algorithm can effectively suppress the low-frequency periodic noise generated by rotating machinery. The computational burden is dispersed among the nodes over the acoustic sensor networks. The frequency of the reference signal is usually identified by a non-acoustic sensor in a NANC system. However, the frequency of the reference signal will be different from the primary noise frequency due to inevitable aging and fatigue accumulation and the control performance of NANC degrades considerably. This phenomenon is referred to as frequency mismatch (FM). In this letter, we analyze the performance degradation of the diffusion FxLMS algorithm due to FM in an NANC system. A theoretical model of the diffusion FxLMS algorithm in the presence of FM is derived based on the equivalent transfer function approach. Extensive simulations are performed to confirm the validity of the theoretical analysis.

关键词： Frequency modulation signal processing algorithms Steady-state Narrowband Frequency control Transfer functions Acoustics Diffusion FxLMS frequency mismatch narrow- band active noise control steady-state analysis

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