Article
Environmental Sciences
Xiaoyu Zhang, Haihong Tao, Ziye Fang, Jian Xie
Summary: A new method is proposed in this paper to address the problem of estimating the direction of arrival (DOA) for mixed uncorrelated and correlated wideband signals in multipath environments. By establishing a novel signal model and dividing the estimator into two parts, the accuracy of DOA estimators for correlated wideband sources has been improved.
Article
Engineering, Electrical & Electronic
Samuel Fernandez-Menduina, Felix Krahmer, Geert Leus, Ayush Bhandari
Summary: This paper aims to address the problem of information loss caused by sensor saturation and clipping. By using a co-design approach with computational arrays, we can overcome the barriers between sensor array hardware and algorithms, enabling encoding and decoding of high-dynamic-range information for various signal processing tasks.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2022)
Article
Engineering, Electrical & Electronic
Yongsung Park, Peter Gerstoft, Jeung-Hoon Lee
Summary: This article presents a method for estimating the direction-of-arrivals of plane waves in a high-frequency region without spatial aliasing using multi-frequency processing. The method utilizes the difference frequency between two high frequencies to process the data effectively. It introduces a MUSIC-based method to handle multiple difference frequencies and snapshots.
IEEE SIGNAL PROCESSING LETTERS
(2022)
Article
Computer Science, Information Systems
Yan Huang, Yanjun Zhang, Jun Tao, Cai Wen, Guisheng Liao, Wei Hong
Summary: In this paper, a novel deep learning framework for super-resolution DOA estimation is proposed. The grid mismatch problem is fully considered in the DL DOA estimation, and the offset between the real DOA and the discrete sampling grid is trained as a part of the network output. By combining on-grid and offset estimation results, accurate off-grid estimation is achieved. The method also incorporates low-level and high-level features to improve training speed and estimation accuracy. Simulation results and real-world testing show the superiority of the proposed method.
SCIENCE CHINA-INFORMATION SCIENCES
(2023)
Article
Engineering, Electrical & Electronic
Ke Wang, Feng Cheng, Jianxin Yi, Xianrong Wan
Summary: Array calibration is crucial for successful array signal processing. Active calibration requires accurate knowledge of the direction of arrival (DOA) of calibration source signals to avoid performance degradation. A novel self-calibration method based on rotation measurement is proposed to address the issue of estimation parameters when performing conventional self-calibration. The method jointly estimates array errors and DOAs of sources through an alternative minimization (AM) algorithm, offering improved robustness and reduced computational complexity.
IEEE SENSORS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Wanlu Shi, Yingsong Li
Summary: This paper proposes an improved uniform linear array (ULA) fitting principle for designing sparse arrays. By introducing adjoint transfer arrays on both sides of a transfer sub-array, an improved adjoint transfer layer is constructed to enhance the lower bound of uniform degrees of freedom (uDOFs). Numerical simulations demonstrate the superiority of the designed arrays in direction-of-arrival (DOA) estimations.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Engineering, Electrical & Electronic
Ziyi Gong, Liang Wu, Zaichen Zhang, Jian Dang, Bingcheng Zhu, Hao Jiang, Geoffrey Ye Li
Summary: This paper introduces a novel scheme for joint TOA and DOA estimation with CFO compensation using large-scale receive antenna arrays. The proposed scheme balances pilot length and estimation performance, providing insights into resolution criteria. Numerical results show that the scheme efficiently eliminates CFO effects and outperforms traditional MDL methods in low SNR conditions.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2021)
Article
Chemistry, Analytical
Ningjun Ruan, Han Wang, Fangqing Wen, Junpeng Shi
Summary: This article discusses various open issues related to DOA estimation for B5G/6G communication networks and provides insights on current advances in arrays, models, sampling, and algorithms. The authors also address directions for future work on the development of DOA estimation.
Article
Automation & Control Systems
Kunkun SongGong, Huawei Chen
Summary: This article explores modal signal processing using circular sensor arrays for speaker localization and proposes a robust indoor speaker localization method that combines least-squares decomposition and spatial processing with a small-sized sensor array. The proposed method addresses issues such as dependency on sensor array characteristics, singularity in the use of Bessel functions, and sensitivity to noisy and reverberant environments, showcasing superior performance in simulations and real-world acoustic environments.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Engineering, Aerospace
Kaijie Xu, Mengdao Xing, Rui Zhang, Hanyu E, Minghui Sha, Weike Nie, Yinghui Quan
Summary: This article presents a method to improve the performance of DOA estimation in array signal processing using a supervised index. The proposed method enhances the DOA estimation performance by modifying the signal subspace. The main feature of the method is the circularly applied feedback of the estimated DOA for refining the estimated subspace.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2022)
Article
Computer Science, Information Systems
Yang Li, Zanhu Huang, Can Liang, Liang Zhang, Yanhua Wang, Junfu Wang, Yi Zhang, Hongfen Lv
Summary: This paper proposes a deep neural network framework with sliding window operation to improve the estimation accuracy of weak sources in high dynamic SNR scenarios. The whole field-of-view is divided into sub-regions, and single-source data is used to train all networks, eliminating the need for training samples and prior information on the number of sources.
Article
Computer Science, Information Systems
Liye Zhang, Weijia Cui, Bin Ba, Chunxiao Jian, Hao Li
Summary: This paper proposes a new method for DOA estimation of sparse array received signals, utilizing DFT spectrum for initial estimation, optimizing estimation accuracy through a new strategy for dividing the over-complete redundant dictionary, and applying Taylor expansion to OMP algorithm in fine angle search process.
Article
Engineering, Electrical & Electronic
Uzma M. Butt, Shoab A. Khan, Anees Ullah, Abdul Khaliq, Pedro Reviriego, Ali Zahir
Summary: A novel design approach for FPGA implementation of the MUSIC algorithm is proposed in this paper, which significantly reduces both FPGA resources and latency.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2021)
Article
Engineering, Electrical & Electronic
Xudong Dong, Xiaofei Zhang, Jun Zhao, Meng Sun
Summary: This paper proposes an extension of the coprime array to practical communication scenarios by considering impulsive noise and non-circular signals. An augmented phased fractional low-order moment (A-PFLOM) is introduced to suppress impulsive noise, and reduced-dimension MUSIC (RD-MUSIC) subspace techniques are applied to estimate the direction of arrival (DOA) of non-circular sources. The proposed method shows better estimation performance in a wide range of impulsive noise environments compared to existing methods.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Chemistry, Analytical
Tiago Troccoli, Juho Pirskanen, Jari Nurmi, Aleksandr Ometov, Jorge Morte, Elena Simona Lohan, Ville Kaseva
Summary: This paper explores the challenge of implementing Direction of Arrival (DOA) methods for indoor localization using IoT devices, with a focus on Bluetooth's direction-finding capability. To overcome the computational limitations of small embedded systems in IoT networks, the paper introduces a customized Unitary R-D Root MUSIC method for L-shaped arrays that leverages Bluetooth's switching protocol. The solution optimizes radio communication system design and uses a root-finding method to simplify complex arithmetic. Experimental results on energy consumption, memory usage, accuracy, and execution time on IoT devices without operating systems and software layers demonstrate the feasibility of the proposed solution, which achieves good accuracy and low execution time.
Article
Engineering, Electrical & Electronic
Zou Deyue, Gao Siyu, Li Xinyue, Zhao Wanlong
Summary: In this paper, an integrated navigation/communication signal is proposed by combining Cyclic Code Shift Keying (CCSK) as a communication signal with traditional Global Navigation Satellite System (GNSS) signal. A fuzzy judging algorithm and segmenting correlation domain are used to improve the transmission robustness of the integrated signal. Additionally, a strategy is proposed to solve the incompatibility problem between the integrated signal and binary communication system using interleaving coding and dual-thresholds optimization. The proposed algorithm significantly improves the fault-tolerant rate and reduces the Bit Error Rate (BER), enhancing the reliability of the communication system.
DIGITAL SIGNAL PROCESSING
(2024)
Article
Engineering, Electrical & Electronic
Guoxing Huang, Yunfei Xiang, Shibiao Deng, Yu Zhang, Jingwen Wang
Summary: This paper proposes a dual-channel cooperative sub-Nyquist sampling system for LFM-BPSK hybrid modulated signal. The system can solve the frequency ambiguity problem caused by low sampling rate and estimate the phases of binary symbols and the positions of discontinuities through self-mixing technology.
DIGITAL SIGNAL PROCESSING
(2024)
Article
Engineering, Electrical & Electronic
A. Yousefian Darani, Y. Khedmati Yengejeh, G. Navarro, H. Pakmanesh, J. Sharafi
Summary: The development and use of network technology have brought society into the internet world, where communication through digital data takes place. However, the protection of digital resources has become a significant challenge, which steganography is seen as a possible solution for. This paper presents an image steganography algorithm that hides a grayscale secret image within an RGB color cover image, with a genetic algorithm used to optimize the selection of suitable hiding places. The proposed method is empirically demonstrated to be effective in terms of transparency, security, and resistance.
DIGITAL SIGNAL PROCESSING
(2024)
Article
Engineering, Electrical & Electronic
Xiao Tan, Zhiwei Yang, Xianghai Li, Yongfei Mao, Di Jiang
Summary: A novel gridless SR-STAP algorithm applicable to a non-ULA with AAPEs is proposed in this study. By establishing the ANM-STAP model and iteratively updating the clutter subspace and AAPEs, the performance of STAP is improved.
DIGITAL SIGNAL PROCESSING
(2024)
Article
Engineering, Electrical & Electronic
Irfan Manisali, Okyanus Oral, Figen S. Oktem
Summary: In this paper, a novel non-iterative deep learning-based reconstruction method for real-time near-field MIMO imaging is proposed. The method achieves high image quality with low computational cost at compressive settings through two stages of processing. A large-scale dataset is also developed for training the neural networks. The effectiveness of the method is demonstrated through experimental data and extensive simulations.
DIGITAL SIGNAL PROCESSING
(2024)
Article
Engineering, Electrical & Electronic
Haibin Li, Dengchao Wu, Wenming Zhang, Cunjun Xiao
Summary: Workplace safety accidents are a pervasive issue worldwide, with 67.95% of construction accidents attributed to the lack of helmet-wearing. Existing helmet detection algorithms suffer from underperformance in real-world scenarios due to various challenges. This study introduces a lightweight helmet detection algorithm, YOLO-PL, which achieves state-of-the-art performance by optimizing network structure and incorporating lightweight modules.
DIGITAL SIGNAL PROCESSING
(2024)
Article
Engineering, Electrical & Electronic
Fen Liu, Jianfeng Chen, Kemeng Li, Jisheng Bai, Weijie Tan, Chang Cai, Muhammad Saad Ayub
Summary: In this paper, a semi-tensor product-based multi-modal factorized multilinear (STP-MFM) pooling method is proposed for information fusion in sentiment analysis. Experimental results demonstrate that the proposed method outperforms baselines in terms of accuracy, training speed, and model complexity.
DIGITAL SIGNAL PROCESSING
(2024)
Article
Engineering, Electrical & Electronic
Xiaoyu Zhao, Xiaoqian Chen, Zhiqiang Gong, Wen Yao, Yunyang Zhang, Xiaohu Zheng
Summary: In this paper, a contrastive enhancement approach is proposed to mine latent prototypes from background regions and leverage latent classes to improve the utilization of similarity information between prototype and query features. The proposed modules, including a latent prototype sampling module and a contrastive enhancement module, significantly improve the performance of state-of-the-art methods for few-shot segmentation.
DIGITAL SIGNAL PROCESSING
(2024)
Article
Engineering, Electrical & Electronic
Xiaoyong Lyu, Baojin Liu, Wenbing Fan, Zhi Quan
Summary: This paper provides an in-depth analysis of the channel estimate model (CEM) in passive radar using orthogonal frequency division multiplexing (OFDM) waveforms. The authors propose a new CEM that takes into consideration the influence of inter-carriers interference (ICI). The theoretical analysis and simulation results support the effectiveness of the new CEM and the proposed method for canceling ICI.
DIGITAL SIGNAL PROCESSING
(2024)
Article
Engineering, Electrical & Electronic
Ruisheng Rana, Jinping Wang, Bin Fang, Weiming Yang
Summary: This paper introduces an improved neighborhood preserving embedding method (NPEAE), which utilizes a linear autoencoder to achieve more accurate and effective data projection from high-dimensional space to low-dimensional space. NPEAE performs better in recognition accuracy compared to other comparative methods.
DIGITAL SIGNAL PROCESSING
(2024)
Article
Engineering, Electrical & Electronic
Yuehao Guo, Xianpeng Wang, Jinmei Shi, Lu Sun, Xiang Lan
Summary: This article presents a fast real-valued tensor propagator method for FDA-MIMO radar. The method improves estimation accuracy by utilizing the original structural information of multidimensional data and eliminates the high computational complexity of high-order singular value decomposition. The proposed algorithm achieves parameter estimation at low snapshots and has lower computational complexity than other algorithms at high snapshots.
DIGITAL SIGNAL PROCESSING
(2024)
Article
Engineering, Electrical & Electronic
Bang Huang, Wen-Qin Wang, Weijian Liu, Shunsheng Zhang, Yizhen Jia
Summary: This paper studies the robust moving target detection problem in FDA-MIMO radar with an unknown covariance matrix in Gaussian clutter. The proposed approach adopts the subspace method and proposes three robust adaptive detectors, which are validated to be effective.
DIGITAL SIGNAL PROCESSING
(2024)
Article
Engineering, Electrical & Electronic
Asutosh Kar
Summary: In this paper, a class of variable step size adaptive algorithms is developed for hybrid narrow-band active noise control (HNANC) systems and compared with the existing state-of-the-art methods. Two algorithms are proposed for HNANC systems operating in multiple noise environments, and their performance is analyzed. The results demonstrate significant improvement in noise reduction compared to the counterparts.
DIGITAL SIGNAL PROCESSING
(2024)
Article
Engineering, Electrical & Electronic
Shouqi Wang, Zhigang Feng
Summary: With the rapid development of artificial intelligence and sensor technology, intelligent fault diagnosis methods based on deep learning are widely used in industrial production. In practical applications, complex noise environments and huge model parameters affect the performance and cost-effectiveness of diagnostic models. In this paper, a lightweight intelligent fault diagnosis model using multi-sensor data fusion is proposed to address these issues. By processing vibration signals from different sensors of rolling bearings using variational mode decomposition (VMD) and designing unique grayscale feature maps based on each intrinsic modal function (IMF) component, the proposed model achieves high accuracy diagnosis in noisy environments while meeting the requirements of small, light, and fast production. The ultra-lightweight GoogLeNet model (ULGoogLeNet) is constructed by adjusting the traditional GoogLeNet structure, and the ultra-lightweight subspace attention module (ULSAM) is introduced to reduce model parameters and enhance feature extraction capability. Experimental results on two datasets demonstrate the effectiveness and superiority of the proposed method.
DIGITAL SIGNAL PROCESSING
(2024)
Article
Engineering, Electrical & Electronic
Jichen Yang, Fangfan Chen, Yu Cheng, Pei Lin
Summary: Recently, there has been significant attention on multi-speaker multimedia speaker recognition (MMSR). This study explores innovative techniques for integrating audio and visual cues from the front-end representations of both speaker's voice and face. Experimental results show that these techniques achieve considerable improvements in the performance of MMSR.
DIGITAL SIGNAL PROCESSING
(2024)