Article
Computer Science, Information Systems
Jin Lu, Guojie Peng, Weichuan Zhang, Changming Sun
Summary: This paper presents an improved particle filter-based track-before-detect (TBD) algorithm for detecting weak targets in low signal-to-noise ratio (SNR) scenarios. The algorithm utilizes a two-layer hypothesis testing approach and outperforms existing TBD algorithms in terms of detection, tracking, and time efficiency.
Article
Geochemistry & Geophysics
Xiang Li, Yan Wang, Bin Qi, Yu Hao
Summary: This article proposes a novel localization approach for the long baseline (LBL) acoustic localization problem by breaking from the traditional two-step paradigm. The approach is based on the track-before-detect (TBD) and particle filtering (PF) theory, which directly determines the target's position. It overcomes the suboptimality of traditional methods by considering the physical basis that the time of arrivals (TOAs) estimated from different buoys correspond to the same target position. The efficacy of the proposed method is demonstrated through simulations and real datasets, showing superior performance under harsh conditions.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Chemistry, Analytical
Wenrong Yue, Feng Xu, Xiongwei Xiao, Juan Yang
Summary: This study proposes a knowledge-aided particle filter track-before-detect algorithm for underwater detection and tracking of diver targets under low signal-to-reverberation ratio conditions in active sonar systems. The algorithm uses original echo data as input and leverages prior knowledge of diver target motion and statistical characteristics to enhance the efficiency of particle filter calculations.
Article
Geochemistry & Geophysics
Xiang Li, Yan Wang, Bin Qi, Yu Hao
Summary: This study addresses the long baseline (LBL) acoustic localization problem by proposing a novel localization framework based on track-before-detect (TBD) theory. The traditional approach ignores the intrinsic correlation between estimated TOAs from different buoys, while the TBD approach allows for directly determining the target location. The experimental results demonstrate the effectiveness of the TBD approach in continuously and accurately tracking targets even under challenging conditions.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Article
Engineering, Electrical & Electronic
Hao Wu, Yongqiang Cheng, Xixi Chen, Zheng Yang, Xiang Li
Summary: In this article, information geometry-based track-before-detect algorithms are proposed to address slow-moving fluctuating target detection issues. These methods exploit the geometric properties of target and clutter tracks on the Hermitian positive definite or power spectrum manifold to integrate inter-frame target information. A scoring function based on information geometry is designed to evaluate candidate trajectories, and a general information geometry-based dynamic programming (DP) algorithm is deduced to obtain trajectories with maximum integration of scoring functions. Experimental results verify the superiority of the proposed methods, achieving a signal-to-clutter ratio improvement of approximately 5.5 dB with real-recorded data.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2023)
Article
Engineering, Electrical & Electronic
Branko Ristic, Robin Guan, Du Yong Kim, Luke Rosenberg
Summary: This paper investigates the detection and tracking of small targets in sea clutter using a high-resolution radar. By incorporating a backward smoothing step, the performance of the Bernoulli filter is improved, leading to enhanced accuracy in detection and tracking.
IET RADAR SONAR AND NAVIGATION
(2022)
Article
Engineering, Electrical & Electronic
Fei Cai
Summary: This paper investigates the challenging problem of detecting and tracking a weak target using a monopulse radar and proposes a track-before-detect (TBD) technique to address this issue. Monte Carlo simulations show that the proposed filter outperforms classical methods and is capable of efficiently detecting and tracking targets even at low signal-to-noise ratios (SNR) as low as -6 dB.
IET SIGNAL PROCESSING
(2022)
Article
Engineering, Electrical & Electronic
Yuhao Chen, Ying Wang, Feng Qu, Wenhui Li
Summary: The paper introduces a graph-based radar target detection algorithm that enhances robustness for temporary target signal loss by optimizing data processing and defining a state transition process, with experimental results confirming its effectiveness.
IEEE SENSORS JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Siqi Qin, Jinshan Ding, Liwu Wen, Ming Jiang
Summary: This article focuses on shadow-based detection and tracking of high-maneuvering targets in video SAR, proposing a JP-DP-TBD algorithm that enhances detection capability and reduces false alarms.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Engineering, Electrical & Electronic
Murat Uney, Paul Horridge, Bernard Mulgrew, Simon Maskell
Summary: This paper focuses on the problem of detecting small and manoeuvring objects using staring array radars. Coherent processing and long-time integration are crucial for addressing the low signal-to-noise/background conditions in this scenario. A Bayesian solution based on a Bernoulli state space model is proposed, which incorporates the likelihood of radar data cubes through the radar ambiguity function. The proposed processing scheme utilizes Bernoulli filtering within expectation maximisation iterations to approximately determine complex reflection coefficients. The effectiveness of the approach is demonstrated through a simulation example.
IEEE SIGNAL PROCESSING LETTERS
(2023)
Article
Geochemistry & Geophysics
Meng Zhang, Lili Dong, Changzhi Tian
Summary: In this study, a detect-track-detect method based on joint multidomain features of objects in infrared marine images is proposed. It includes a differential Gaussian local peak single-frame detection method to identify potential objects, a dual-threshold pipeline filter multiframe selection and trajectory prediction to remove false objects and predict missing objects' positions, and a redetection of predicted patches to recover missing objects. Experiments demonstrate that this method improves the stability and accuracy of infrared sequence object detection while maintaining real-time performance.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Article
Engineering, Aerospace
Yi Zhou, Hang Su, Shuai Tian, Xiaoming Liu, Jidong Suo
Summary: This article addresses the problem of tracking weak and extended targets in clutter for marine radar systems and proposes a solution using multiple kernelized correlation filters (MKCFs). Compared to other amplitude-based methods, this approach performs better in detecting and tracking extended targets.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2022)
Article
Engineering, Multidisciplinary
Guohui Li, Yongming Hou, Hong Yang
Summary: The proposed differential double coupled Duffing oscillator method provides a more intuitive way to judge large scale states and overcomes frequency limitations, showing high signal-to-noise ratio and universality in detecting various background signals.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Environmental Sciences
Xiangyu Peng, Qiang Song, Yue Zhang, Wei Wang
Summary: Due to the limited transmission gain of ubiquitous radar systems, a long-time coherent integration method is necessary for range-Doppler (RD) analysis. High-speed and high-maneuver capabilities of targets introduce challenges such as range migration (RM), Doppler frequency migration (DFM), and velocity ambiguity (VA) in the RD domain, posing significant difficulties in target detection and tracking. This study proposes a hybrid integration approach to address these complexities while maintaining integration efficiency.
Article
Engineering, Aerospace
Liangliang Wang, Gongjian Zhou, Thiagalingam Kirubarajan
Summary: In this paper, a pseudo-spectrum based multiframe Track-Before-Detect (TBD) method in mixed coordinates is proposed to address the issues of model mismatch and target envelope degradation in traditional TBD methods. Additionally, a velocity filter bank based on pseudo-spectrum in mixed coordinates and a parameter estimation method using characteristics of integrated envelope are introduced to cope with unknown target velocity and improve target position and velocity estimation.
CHINESE JOURNAL OF AERONAUTICS
(2022)
Article
Acoustics
Cailiang Zhang, Zhihui Lai, Zhisheng Tu, Hanqiu Liu, Yong Chen, Ronghua Zhu
Summary: This paper proposes two single-parameter-adjusting SR models to optimize the output performance of SR systems. The effects of the proposed models on SR output under different parameters and signals are investigated through numerical simulations, and their feasibility is verified through experimental results. The research results are of great significance for guiding the design of tri-stable SR models and the application of SR-based signal processing in the context of big data.
Article
Acoustics
Shaoqiong Yang, Hao Chang, Yanhui Wang, Ming Yang, Tongshuai Sun
Summary: In this study, a suspension system based on phononic crystals is designed for vibration isolation of acoustic loads in underwater gliders. The vibration properties of the phononic crystals and the effects of physical parameters on the underwater attenuation zones are investigated. Vibration tests show that the phononic crystal suspension system has a stable vibration isolation effect in the frequency range of 120-5000 Hz.
Article
Acoustics
Xuebin Zhang, Jun Zhang, Tao Liu, Ning Hu
Summary: This study proposes a tunable metamaterial beam to isolate flexural waves. A genetic algorithm-based size optimization is used to obtain a broad low-frequency bandgap. The tunability of the beam is achieved by attaching different numbers of permanent magnets to change the mass of the resonators. Additionally, ultra-broadband flexural wave attenuation is achieved by forming a gradient metamaterial beam based on the rainbow effect. Numerical and experimental results confirm the good flexural wave attenuation ability of the proposed beam.
Article
Acoustics
Luca Rapino, Francesco Ripamonti, Samanta Dallasta, Simone Baro, Roberto Corradi
Summary: This paper presents a method for simulating tyre/road noise using equivalent monopoles, including the synthesis of monopoles through an inverse problem approach and the use of an ISO 10844 road replica for laboratory testing. The method combines acoustic finite element models and numerical simulations of vehicles, and the results are validated by comparing them with measured data.
Article
Acoustics
Xiaoyan Zhu, Tin Oberman, Francesco Aletta
Summary: This paper explores the definition of acoustical heritage and proposes a multidimensional definition based on interviews with experts and detailed analysis of the data.
Article
Acoustics
Faeez Masurkar, Saurabh Aggarwal, Zi Wen Tham, Lei Zhang, Feng Yang, Fangsen Cui
Summary: This research focuses on estimating the elastic constants of orthotropic laminates using ultrasonic guided waves and inverse machine learning models. The results show that this approach has the potential to accurately predict the elastic constants of a material and reduce computational time.
Article
Acoustics
Feng Xiao, Haiquan Liu, Jia Lu
Summary: Diagnostic methods for cardiovascular disease based on heart sound classification have been widely studied due to their noninvasiveness, low-cost, and high efficiency. However, existing research often faces challenges such as the nonstationarity and complexity of heart sound signals, leading to limited capability of neural networks to extract discriminative features. To address these issues, this study proposes a novel convolutional neural network that combines 1D convolution and 2D convolution, and introduces an attention mechanism to enhance feature extraction capability. The study also explores the advantages and disadvantages of combining deep learning features with manual features, and adopts an evolving fuzzy system for decision-making interpretability.
Article
Acoustics
Hong Xu, Zhengyao He, Qiang Shi, Yushi Wang, Bo Zhang
Summary: This paper presents the development of a directional segmented ring transmitting transducer that can radiate sound waves in any horizontal region. The study focuses on the structure of the segmented ring transducer, its radiation sound field characteristics, and the beam pattern control method based on modal synthesis. The authors propose orthogonal beam pattern functions for adjusting steering angles and establish a three-dimensional finite element model to simulate the transmitting beam patterns. Experimental measurements and tests validate the effectiveness of the proposed transducer, showcasing its ability to steer the beam patterns to different directions.
Article
Acoustics
Jirui Yang, Shefeng Yan, Di Zeng, Gang Tan
Summary: This paper proposes an improved domain adaptation framework, self-supervised learning minimax entropy, to enhance the recognition performance of underwater target recognition models. The experimental results demonstrate that applying domain adaptation methods can effectively improve the recognition accuracy of the models under various marine conditions.
Article
Acoustics
Zonghan Sun, Jie Tian, Yuhang Zheng, Xiaocheng Zhu, Zhaohui Du, Hua Ouyang
Summary: This paper analyzes the noise reduction method of installing a sinusoidal-shaped inlet duct on a cooling fan through theoretical and experimental analysis of the acoustic mode modulation. The study establishes the correlation between the free field noise and acoustic mode of the fan rotor and the unsteady forces on the rotor blade surface. The results show that the sinusoidal-shaped inlet duct achieves greater noise reduction compared to a straight duct, especially at the blade passing frequency and its first harmonic.
Article
Acoustics
Min Li, Rumei Han, Hui Xie, Ruining Zhang, Haochen Guo, Yuan Zhang, Jian Kang
Summary: This study is part of a global collaboration to translate and standardise soundscape research. A reliable questionnaire for soundscape characterisation in Mandarin Chinese was developed and validated. The study found that salient sound sources become the focus of attention for individuals in urban open spaces, and the perception is also influenced by the acoustic characteristics of the soundscape. Certain types of sound sources play a more important role in soundscape perception.
Article
Acoustics
Arezoo Talebzadeh, Dick Botteldooren, Timothy Van Renterghem, Pieter Thomas, Dominique Van de Velde, Patricia De Vriendt, Tara Vander Mynsbrugge, Yuanbo Hou, Paul Devos
Summary: This study proposes a sound selection methodology to enhance the soundscape in nursing homes and reduce BPSD by analyzing sound characteristics and recognition methods. The results highlight the sound characteristics that lead to positive responses, while also pointing out the need for further studies to understand which sounds are most suitable for people with dementia.
Article
Acoustics
Yang Yang, Yongxin Yang, Zhigang Chu
Summary: This paper introduces a grid-free compressive beamforming method compatible with arbitrary linear microphone arrays, and demonstrates the correctness and superiority of the proposed method through examples. Monte Carlo simulations are performed to reveal the effects of source coherence, source separation, noise, and number of snapshots.
Article
Acoustics
Sukru Selim Calik, Ayhan Kucukmanisa, Zeynep Hilal Kilimci
Summary: Computer-Aided Language Learning (CALL) is growing rapidly due to the importance of acquiring proficiency in multiple languages for effective communication. In the field of CALL, the detection of mispronunciations is vital for non-native speakers. This research introduces a novel framework using audio-centric transformer models to detect mispronunciations in Arabic phonemes. The results demonstrate that the UNI-SPEECH transformer model yields notable classification outcomes in Arabic phoneme mispronunciation detection. The comprehensive comparison of these transformer models provides valuable insights and guidance for future investigations in this domain.
Article
Acoustics
Yi-Yang Ni, Fei-Yun Wu, Hui-Zhong Yang, Kunde Yang
Summary: This paper proposes an improved method for compressive sensing by introducing a self training dictionary scheme and a CS reconstruction method based on A*OLS, which enhances the sparse representation performance of propeller signals.