Article
Engineering, Civil
Douglas A. Abraham
Summary: This article explores the application of product array processing in signal phase estimation, proposing a weak-signal maximum-likelihood estimator for estimating the phase of narrowband signals in product array processors. The study found that in independent Gaussian noise, the performance loss of the product array processing phase estimator compared to the full-array ML phase estimator does not exceed 1-dB SNR.
IEEE JOURNAL OF OCEANIC ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
Gengxin Ning, Shujia Zhang, Jun Zhang, Cui Yang
Summary: This paper presents a velocity-independent 2-D direction-of-arrival (DOA) estimation algorithm for eliminating the influence of acoustic velocity variable in underwater environment. By utilizing three parallel uniform linear arrays and matrix signal processing, the algorithm removes the acoustic velocity variable and estimates the azimuth and elevation angles of the target without the need for additional search or matching procedures. Simulation results show that the proposed algorithm outperforms traditional 2-D DOA algorithms in unknown acoustic velocity conditions, with lower computational complexity compared to velocity-independent 2-D DOA algorithms.
IET SIGNAL PROCESSING
(2022)
Article
Engineering, Electrical & Electronic
Baohua Zhang, Guangyi Liu, Ou Li, Zhixiang Shen, Fengtong Mei
Summary: In this article, a novel sparse array with seven subarrays (SA-7S) is proposed, which can generate a hole-free uniform difference co-array. The sensor locations of the SA-7S array are uniquely determined by a closed-form expression and the number of achievable degrees of freedom is analytically presented as well. Theoretical analysis and simulations demonstrate that the SA-7S array can provide a higher number of degrees of freedom and better performance in terms of mutual coupling and direction of arrival estimation.
IET RADAR SONAR AND NAVIGATION
(2023)
Article
Engineering, Electrical & Electronic
Zonglong Bai, Liming Shi, Jinwei Sun, Mads Graesboll Christensen
Summary: This paper proposes a method for recovering complex sparse signals, based on a hierarchical model with adaptive Laplace priors and integrated with the space alternating approach to reduce computational complexity. Experiments demonstrate that this method achieves better recovery performance for different types of complex signals compared to state-of-the-art techniques.
IET SIGNAL PROCESSING
(2023)
Article
Computer Science, Information Systems
Yueheng Li, Xueyun Long, Lucas Giroto de Oliveira, Joerg Eisenbeis, Mohamad Basim Alabd, Sven Bettinga, Xiang Wan, Tie Jun Cui, Thomas Zwick
Summary: With the development of wireless communication, the MIMO architecture has been proven to be a solution for higher data rates. The PM is a promising antenna array concept with advantages of low cost and power consumption. However, the experimental investigation of combining PMs with modern wireless communication systems is still lacking.
IEEE SYSTEMS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Jian Yang, Yuwei Tu, Jian Lu, Zhiwei Yang
Summary: A robust adaptive beamforming method is proposed, which improves the performance of adaptive arrays through covariance matrix reconstruction and subspace decomposition. Simulation results demonstrate its superior performance under multiple mismatches and different signal-to-noise ratios.
IEEE SENSORS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Sebastian Semper, Michael Doebereiner, Christian Steinmetz, Markus Landmann, Reiner S. Thomae
Summary: Multidimensional channel sounding is used to measure the geometrical structure of mobile radio propagation by estimating the parameters of a multipath data model. The estimation is done using observations in frequency, time, and space, and the maximum likelihood estimation framework allows for high resolution in all dimensions. An appropriate parametric data model is necessary to accurately represent the multipath propagation, as well as a device data model that comes from calibration measurements. The extension of the multidimensional Richter maximization approach (RIMAX) parameter estimation framework with proper frequency responses shows better performance for higher relative bandwidths compared to conventional RIMAX implementation.
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
(2023)
Article
Engineering, Electrical & Electronic
Yalin Wang, Xihan Chen, Yunlong Cai, Benoit Champagne, Lajos Hanzo
Summary: This paper investigates the challenges in achieving high channel estimation accuracy and reducing hardware cost and power dissipation in massive MIMO systems. By optimizing pilot sequences, the number of quantization bits and the hybrid receiver combiner, we address the channel estimation problem in the uplink of multiuser massive MIMO systems. Using fractional programming techniques, we propose novel algorithms for solving the associated mixed-integer problems.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Xiangrong Wang, Maria Sabrina Greco, Fulvio Gini
Summary: In this work, a novel strategy of adaptive sparse array beamformer design, termed regularized complementary antenna switching (RCAS), is proposed to enhance interference suppression by swiftly adapting array configuration and excitation weights according to the dynamic environment. The method involves designing a set of deterministic complementary sparse arrays with good quiescent beampatterns, followed by calculating and reconfiguring an adaptive sparse array tailored for the specific environment based on information extracted from the full array data. The RCAS is formulated as an exclusive cardinality-constrained optimization, proving its effectiveness through rigorous theoretical analysis and simulation results.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2021)
Article
Automation & Control Systems
Xinyu Li, Feng Chen, Qing Shi, Yue Cao, Fei Yan, Bingpeng Zhou
Summary: This paper investigates the problem of robust distributed estimation over dynamic and streaming graph signals, and proposes a new d-MC algorithm to overcome the vulnerability of existing methods to nonGaussian noise based on the Mean-Square-Error criterion. Simulation results demonstrate the desirable performance of the proposed algorithm in various noise environments.
Article
Engineering, Electrical & Electronic
Zikai Wang, Yun Liu, Ruiliang Song, Ning Liu, Qilian Liang
Summary: This paper introduces a new type of nonlinear sparse sensor array called sparse convolutional array, which improves the performance of DOA estimation by adding sensors while reducing the number of physical sensors.
EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING
(2022)
Review
Computer Science, Information Systems
Ibrahim Aboumahmoud, Ali Muqaibel, Mohammad Alhassoun, Saleh Alawsh
Summary: Two-dimensional sparse arrays play a crucial role in localization applications, providing superior direction-of-arrival estimation performance with limited sensors. Research efforts in designing 2D sparse arrays have increased, but lack coordination, resulting in repetitions and conflicting claims. This paper establishes a model for 2D-DoA estimation, consolidates performance metrics, and categorizes existing works, aiming to address fundamental problems and discuss solutions for improving estimation performance.
Article
Engineering, Electrical & Electronic
Yao Zhao, Qingsong Liu, He Tian, Mingfan Luo, Bingo Wing-Kuen Ling, Zhe Zhang
Summary: This paper addresses the problem of minimum variance distortionless response (MVDR) robust adaptive beamforming, focusing on optimal estimations for the desired signal steering vector and the interference-plus-noise covariance (INC) matrix. A new tightened semidefinite relaxation (SDR) method is introduced to provide globally optimal solutions for nonconvex challenges, with a sequential convex approximation method as an alternative for local optimization. Simulations demonstrate that the proposed MVDR beamformers, based on both the steering vector and INC matrix, outperform those relying solely on steering vector estimation.
ELECTRONICS LETTERS
(2023)
Article
Engineering, Electrical & Electronic
Yao Zhao, Qingsong Liu, He Tian, Mingfan Luo, Bingo Wing-Kuen Ling, Zhe Zhang
Summary: This paper addresses the general minimum variance distortionless response (MVDR) robust adaptive beamforming problem by focusing on the optimal estimations for the desired signal steering vector and the interference-plus-noise covariance (INC) matrix. A new tightened semidefinite relaxation (SDR) method is proposed to provide globally optimal solutions for nonconvex challenges, with a sequential convex approximation method as an alternative for local optimization. Simulations demonstrate that the proposed MVDR beamformers, based on both the steering vector and INC matrix, outperform those relying solely on steering vector estimation.
ELECTRONICS LETTERS
(2023)
Article
Engineering, Electrical & Electronic
Hiroshi Kikuchi, Eiichi Yoshikawa, Tomoo Ushio, Yasuhide Hobara
Summary: In December 2017, a dual-polarized phased-array weather radar was deployed in Tokyo for precipitation observations, featuring high temporal resolution and improved rain rate estimation capabilities. By developing an adaptive beamforming method, the radar achieved superior clutter suppression compared to conventional methods.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Environmental Sciences
Artem G. Lim, Sergey Loiko, Daria M. Kuzmina, Ivan Krickov, Liudmila S. Shirokova, Sergey P. Kulizhsky, Sergey N. Vorobyev, Oleg S. Pokrovsky
Summary: The study found that dissolved organic carbon (DOC), alkali and alkaline-earth metals, sulfate, phosphorus, and other substances were significantly more concentrated in peat ice compared to peat porewaters from the active layer. During full freezing of the soil column in winter, there was a local maximum of enrichment in certain substances located 30-50 cm below the active layer. This research highlights the importance of assessing the consequences of permafrost thaw on surface aquatic systems.
Article
Multidisciplinary Sciences
Jan Karlsson, Svetlana Serikova, Sergey N. Vorobyev, Gerard Rocher-Ros, Blaize Denfeld, Oleg S. Pokrovsky
Summary: High-latitude regions, particularly Western Siberia, play a crucial role in the carbon cycle and climate system. Emission of carbon from inland waters, such as rivers and lakes, exceeds carbon export to the Arctic Ocean and is a major contributor to the regional carbon balance. This highlights the importance of coupled land-water studies in understanding the contemporary carbon cycle and its response to warming.
NATURE COMMUNICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Hongyang Chen, Fauzia Ahmad, Sergiy Vorobyov, Fatih Porikli
Summary: The versatility of tensor decompositions in data analysis and signal processing, especially in wireless communications and MIMO radar, provides greater flexibility in data properties constraints and allows extraction of more general latent data components than matrix-based methods. Tensor analysis also offers the ability to exploit higher-dimensional signal structures in MIMO radar applications.
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
(2021)
Editorial Material
Engineering, Electrical & Electronic
Hongyang Chen, Sergiy A. Vorobyov, Hing Cheung So, Fauzia Ahmad, Fatih Porikli
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
(2021)
Article
Environmental Sciences
Rinat M. Manasypov, Oleg S. Pokrovsky, Liudmila S. Shirokova, Yves Auda, Nadezhda S. Zinner, Sergey N. Vorobyev, Sergey N. Kirpotin
Summary: The chemical composition of thermokarst lake ecosystem components is important for understanding current climate change and permafrost thaw. Macrophytes play a crucial role in controlling nutrients and toxicants in lake water, with accumulation patterns varying among different plant species. Future climate warming may lead to increased uptake of heavy metals and lithogenic elements by macrophytes, impacting nutrient transport from soils to lakes and rivers.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Environmental Sciences
Sergey N. Vorobyev, Yuri Kolesnichenko, Mikhail A. Korets, Oleg S. Pokrovsky
Summary: The transport of major and trace elements by rivers in permafrost-affected regions plays a crucial role in the response of circumpolar aquatic ecosystems to climate warming. Spatial patterns in element concentrations were observed in the Lena River basin during the peak of spring flood, with specific variations in solute distribution based on landscape parameters. The study also highlighted the influence of changes in dominant rock types from carbonate to silicate on the downstream concentration of labile major and trace elements, as well as the increasing importance of dissolved organic carbon and low-soluble elements in certain parts of the river basin.
Article
Engineering, Electrical & Electronic
Yang Jing, Junli Liang, Sergiy A. Vorobyov, Xuhui Fan, Deyun Zhou
Summary: This paper aims to jointly design transmit waveform and mismatched filter to achieve low sidelobe level in radar systems, using an Lp-norm metric for PC model and a new iterative method based on Dinkelbach's scheme and majorization minimization method. Numerical examples demonstrate that waveforms and filters designed by the proposed method produce lower PSL than existing techniques.
Article
Engineering, Electrical & Electronic
Jari Miettinen, Sergiy A. Vorobyov, Esa Ollila
Summary: The paper addresses the importance of modeling errors in adjacency matrices for graph signal processing and introduces practically justifiable graph error models. Through analytical and numerical studies, the effects of graph errors on the performance of GSP methods are explored.
Proceedings Paper
Acoustics
Wanlu Shi, Yingsong Li, Sergiy A. Vorobyov
Summary: This paper proposes a general sparse array design principle, called uniform linear array fitting, which designs sparse arrays with feasible difference coarrays by concatenating sub-ULAs. The polynomial model is utilized to study cases where the array is composed of multiple sub-ULAs, and an example is presented to demonstrate that the uniform linear array fitting enables the design of arrays with closed-form expressions, low coupling leakage, and long consecutive DCAs.
2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021)
(2021)
Proceedings Paper
Acoustics
Feng Xu, Sergiy A. Vorobyov
Summary: This paper proposes a constrained tensor decomposition method for 2D DOA estimation in TB MIMO radar with subarrays. By utilizing the inner structure of factor matrix, the method successfully estimates the target DOA and computes angular information to enhance the robustness of the estimation. Simulation results confirm the effectiveness of the proposed approach.
2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021)
(2021)
Proceedings Paper
Acoustics
Majdoddin Esfandiari, Sergiy A. Vorobyov
Summary: The paper addresses the challenging DOA estimation problem in the presence of coherent sources, low sample size, and low signal-to-noise ratio. Two new methods, ES ESPRIT and EU ESPRIT, are developed to generate DOA candidates and discretely select sources. Numerical results demonstrate the superiority of EU ESPRIT in improving threshold performance and separating closely located sources with small sample sizes compared to existing methods.
2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021)
(2021)
Article
Ecology
Sergey N. Vorobyev, Jan Karlsson, Yuri Y. Kolesnichenko, Mikhail A. Korets, Oleg S. Pokrovsky
Summary: Research has found that pCO(2) in tributaries increases with decreasing mean annual temperature and increasing permafrost in permafrost-affected regions of central and eastern Siberia, positively correlated with carbon stock in soil, proportion of deciduous needleleaf forest, and riparian vegetation. Calculations showed that carbon emissions from lotic waters of the Lena watershed are comparable to those in other permafrost-affected rivers in Siberia.
Proceedings Paper
Acoustics
Feng Xu, Matthew W. Morency, Sergiy A. Vorobyov
Summary: This paper proposes a novel DOA estimation algorithm based on tensor decomposition for collocated transmit beamspace MIMO radar, which increases the signal to noise ratio by introducing the flipped-conjugate version of the transmit beamspace matrix. The alternating least squares (ALS) algorithm is utilized to find tensor components and grating lobes can be eliminated by finite trials of spectrum search. The performance of the proposed DOA estimation method outperforms several conventional algorithms in terms of accuracy and resolution.
28TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO 2020)
(2021)
Proceedings Paper
Acoustics
Yang Jing, Junli Liang, Sergiy A. Vorobyov, Xuhui Fan, Deyun Zhou
Summary: The paper focuses on joint design of transmit waveform and mismatched filter to achieve low sidelobe level for improving the resolution of pulse compression. A new iterative algorithm is developed to solve the optimization problem, based on using Dinkelbach's scheme together with majorization minimization method. Numerical examples demonstrate the effectiveness of the proposed method in producing lower peak sidelobe level than existing counterparts.
28TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO 2020)
(2021)
Article
Engineering, Electrical & Electronic
Jari Miettinen, Eyal Nitzan, Sergiy A. Vorobyov, Esa Ollila
Summary: This paper fills the gap in blind source separation research for graph signals with two contributions. The results show that utilizing both graph structure and non-Gaussianity provides a more robust approach, which is demonstrated to be more efficient in separating non-Gaussian graph signals.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2021)
