检索结果-内蒙古大学图书馆

Learning Dynamic-Sensitivity Enhanced Correlation Filter With Adaptive Second-Order Difference Spatial Regularization for UAV Tracking

引用

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2025年第5期26卷 7211-7230页

作者： Yu, Yu-Feng Chen, Zhongsen Zhang, Yang Zhang, Chuanbin Ding, Weiping Guangzhou Univ Dept Stat Guangzhou 511370 Peoples R China Univ Macau Dept Comp & Informat Sci Macau Peoples R China Zhaoqing Univ Sch Comp Sci & Software Zhaoqing 526061 Peoples R China Nantong Univ Sch Artificial Intelligence & Comp Sci Nantong 226019 Peoples R China City Univ Macau Fac Data Sci Macau Peoples R China

Discriminative correlation filter (DCF)-based tracking algorithms continue to advance in the field of UAV tracking due to their computational efficiency. The idea of integrating the advantages of historical information and response adjustments into the CF tracking framework is continuously being developed. However, maintaining the stability of mobile video tracking in highly dynamic environments is extremely challenging. This difficulty arises from frequent changes in targets and backgrounds, as well as the stochastic noise generated by the photon-counting process in sensors. In addition, the inconsistent rates of these changes are often overlooked and require further scrutiny. In this paper, we propose a dynamic sensitivity enhanced correlation filter with adaptive second-order difference spatial regularization to address the issue of inconsistent motion rates in dynamic videos. We use the non-local means algorithm to denoise template images before feature extraction, improving the discriminative power of target contours. Then, we incorporate the proposed dynamic-sensitivity error method into CF learning and employ a novel adaptive second-order difference spatial regularization to simultaneously optimize the filter coefficients and spatial regularization weights. This regularization effectively works in synergy with the dynamic-sensitivity error strategy. Furthermore, an additional ADMM optimizer is introduced to derive the solution, thereby improving the convergence and computational efficiency of the algorithm. This algorithm supports the adjustment of filter updates in dynamic environments by balancing consistency with previous filter templates and flexibility to accommodate rapid target changes. By conducting extensive experiments on three challenging UAV tracking databases, we compare the proposed model with existing models. The experimental results demonstrate our superior performance. Code is released at: https://***/Johnsonirene/LDECF.

关键词： Target tracking Autonomous aerial vehicles filtering algorithms Correlation Feature extraction Accuracy Tracking Real-time systems Visualization Vehicle dynamics Correlation filters dynamic sensitivity UAV tracking non-local means second-order difference weights

来源：评论

学校读者我要写书评

暂无评论

Selective Partial-Update Widely Linear Geometric-Algebra NLMS

引用

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2024年第9期71卷 4381-4385页

作者： Wang, Wenyuan Dogancay, Kutluyil Jiangnan Univ Sch Internet Things Engn Wuxi 214122 Peoples R China Univ South Australia UniSA STEM Mawson Lakes SA 5095 Australia

Adaptive filters based on geometric algebra have demonstrated remarkable success in various applications, such as computer vision, data fusion, and linear prediction, particularly when dealing with high-dimensional multivectors as unknown parameters. However, the extensively used geometric-algebra adaptive filters, especially those applied to widely linear signals, often present significant computational complexity challenges. To address this, the partial-update widely linear geometric algebra least mean squares algorithm was introduced, but it unfortunately exhibits an underwhelming convergence performance. In this brief we develop a new selective partial update geometric-algebra normalized least mean square (NLMS) algorithm, along with its set-membership extension, to improve the convergence performance of partial-update algorithms. Simulation studies conducted to examine the performance of these proposed algorithms, specifically for multivector and quaternion-valued inputs, corroborate their effectiveness and improved performance.

关键词： Algebra Adaptive filters Point cloud compression filtering algorithms Convergence Vectors Three-dimensional displays Adaptive filter geometric algebra selective partial updates

来源：评论

学校读者我要写书评

暂无评论

Joint Design of Transmit Waveform and Receive Filter for Cross Ambiguity Function Synthesis

引用

IEEE WIRELESS COMMUNICATIONS LETTERS 2024年第3期13卷 839-843页

作者： Qiu, Xiangfeng Yang, Chen Jiang, Weidong Liu, Yongxiang Natl Univ Def Technol Coll Elect Sci & Technol Changsha 410073 Peoples R China

The cross-ambiguity function (CAF) is a crucial performance evaluation metric for transmit waveform. To improve the interference suppression performance in the wireless sensing field, we address the problem of synthesizing radar CAF by jointly designing the transmit waveform and receive filter in this letter. We first establish the joint design problem as a non-convex fractional problem by maximizing the signal-to-interference plus noise ratio (SINR) under practical constraints. To overcome the challenges posed by the peak-to-average ratio (PAR) constraint, we then propose an novel iterative optimization algorithm based on the Majorization-Minimization (MM) framework. This algorithm synthesizes the transmit waveform and receive filter alternately and efficiently. Finally, we conduct numerical simulations with different parameters to demonstrate the effectiveness of our proposed CAF synthesizing algorithm.

关键词： Interference Signal to noise ratio Doppler effect Radar Peak to average power ratio Microwave filters filtering algorithms Cross ambiguity function waveform optimization majorization-minimization SINR maximization constant modulus constraint

来源：评论

学校读者我要写书评

暂无评论

Frequency-Constrained Iterative Adversarial Attacks for Automatic Modulation Classification

引用

IEEE COMMUNICATIONS LETTERS 2024年第12期28卷 2734-2738页

作者： Chen, Yigong Qiao, Xiaoqiang Zhang, Jiang Zhang, Tao Du, Yihang Nanjing Univ Informat Sci & Technol Sch Elect & Informat Engn Nanjing 210044 Peoples R China Natl Univ Def Technol Res Inst 63 Nanjing 210007 Peoples R China

Although adversarial attacks present a significant threat to intelligent models based on deep learning (DL) for automatic modulation classification (AMC). However, the existing works for electromagnetic signal adversarial attacks introduce high frequency components in the frequency domain, which causes spectral mismatch and glitch problems, degrading the attack success rate after transmission through a band-limited channel. In this letter, we propose a frequency-constrained iterative adversarial attacks (FCIAA) algorithm which can suppress the high frequency components and optimize adversarial perturbations during the iterative process to alleviate such problems. The experiments using qualitative and quantitative indicators demonstrate that the proposed algorithm can effectively constrain out-of-band perturbation energy, which improves both the time and frequency domain concealment quality of the adversarial signals and enhances adversarial attacks effect.

关键词： Perturbation methods Low-pass filters filtering algorithms Frequency-domain analysis Modulation Classification algorithms Wireless communication Bandwidth Vectors Transmitters Automatic modulation classification adversarial attacks low-pass filter wireless security deep learning

来源：评论

学校读者我要写书评

暂无评论

Track Coalescence and Repulsion in Multitarget Tracking: An Analysis of MHT, JPDA, and Belief Propagation Methods

IEEE OPEN JOURNAL OF SIGNAL PROCESSING

引用

IEEE OPEN JOURNAL OF SIGNAL PROCESSING 2024年 5卷 1089-1106页

作者： Kropfreiter, Thomas Meyer, Florian Crouse, David F. Coraluppi, Stefano Hlawatsch, Franz Willett, Peter Univ Calif San Diego Scripps Inst Oceanog La Jolla CA 92037 USA Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 92037 USA Naval Res Lab Washington DC 20375 USA Syst & Technol Res Woburn MA 01801 USA TU Wien Inst Telecommun A-1040 Vienna Austria Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

Joint probabilistic data association (JPDA) filter methods and multiple hypothesis tracking (MHT) methods are widely used for multitarget tracking (MTT). However, they are known to exhibit undesirable behavior in tracking scenarios with targets in close proximity: JPDA filter methods suffer from the track coalescence effect, i.e., the estimated tracks of targets in close proximity tend to merge and can become indistinguishable, while MHT methods suffer from an opposite effect known as track repulsion, i.e., the estimated tracks of targets in close proximity tend to repel each other in the sense that their separation is larger than the actual distance between the targets. In this paper, we review the JPDA filter and MHT methods and discuss the track coalescence and track repulsion effects. We also consider a more recent methodology for MTT that is based on the belief propagation (BP) algorithm. We argue that BP-based MTT does not exhibit track repulsion because it is not based on maximum a posteriori estimation, and that it exhibits significantly reduced track coalescence because certain properties of the BP messages related to data association encourage separation of target state estimates. Our theoretical arguments are confirmed by numerical results for four representative simulation scenarios.

关键词： Target tracking Vectors Probabilistic logic filtering algorithms Estimation Electronic mail Probability density function Multitarget tracking joint probabilistic data association JPDA multiple hypothesis tracking MHT belief propagation track coalescence track repulsion

来源：评论

学校读者我要写书评

暂无评论

A New Switching MVC Algorithm for Active Impulsive Noise Control

引用

IEEE EMBEDDED SYSTEMS LETTERS 2024年第3期16卷 271-274页

作者： Maya, Xochitl Soto, Adrian E. Vazquez, Angel A. Avalos, Juan G. Sanchez, Giovanny Sanchez, Juan C. Inst Politecn Nacl ESIME Culhuacan Mexico City 04440 Mexico

In realistic sound scenarios, cutting-edge active noise control (ANC) systems still suffer critical instabilities since these systems works under impulsive noise signals. To decrease the negative impact of this noise, several authors have made extraordinary efforts to develop efficient algorithms in terms of convergence speed and misadjustment. However, these algorithms still exhibits limited convergence capabilities. In this letter, we present for the first time, the development of a switching algorithm based on the maximum versoria criterion (MVC) algorithm. Our results demonstrate that the proposed switching algorithm exhibits good convergence properties while maintaining a lower-computational cost when compared with existing algorithms.

关键词： filtering algorithms Adaptive filters Finite impulse response filters Switches Convergence Computational efficiency Signal processing algorithms Active noise control (ANC) adaptive filtering impulsive noise maximum versoria criterion (MVC) algorithm switching algorithm

来源：评论

学校读者我要写书评

暂无评论

GaLAM: Two-Stage Outlier Detection Algorithm

引用

IEEE ACCESS 2025年 13卷 76135-76144页

作者： Lu, Xiaojun Yan, Zhe Fan, Ziyun Northeastern Univ Coll Sci Shenyang 110819 Peoples R China

Image matching aims to establish correspondences between images and estimate relative transformations, serving as a critical component in many geometric computer vision tasks. However, due to the limitations of descriptors and the presence of moving objects in the target region, results from nearest-neighbor matching often include numerous outliers. Recently, significant efforts have focused on effectively filtering these outliers to improve image matching performance. In this paper, we propose Globally-and-Locally-Affine Matching (GaLAM), a two-stage outlier detection method. In the first stage, GaLAM optimizes the edge features of Adaptive Locally Affine Matching (AdaLAM) and replaces the statistical neighborhood-based approach with classical geometric deviation metrics. In the second stage, Progressive Sample Consensus (PROSAC) is used to sample seed points that align with the fundamental matrix, followed by filtering outliers based on projection deviation. This approach enhances the model's robustness in complex scenes, particularly in scenarios with moving objects in the target region. We evaluated GaLAM on diverse datasets, and the results demonstrate that our method achieves significant improvements over AdaLAM in most scenarios.

关键词： Matched filters Image matching Silicon Optical filters filtering algorithms Anomaly detection Robustness Accuracy Three-dimensional displays Estimation outlier detection GaLAM

来源：评论

学校读者我要写书评

暂无评论

Application study of PointNet++ and hybrid filtering based point cloud denoising and segmentation algorithms for Blisk

Application study of PointNet++ and hybrid filtering based p...

引用

World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM)

作者： Xiaohang Gan Libin Tan Xiaoyi Wang School of mechanical engineering Anhui University of Technology Ma'anshan China

ISBN: (纸本)9781665473705

In the process of collecting 3D point cloud data of aviation blisk, it is inevitable to collect various noise points and background point cloud data, which will affect the subsequent 3D reconstruction process. Therefore, how to extract the effective blisk point cloud information and retain the accurate structural features as much as possible is an important step in the preprocessing of the overall blisk 3D reconstruction. To this end, this paper proposes a hybrid filtering algorithm to denoise the single-view blisk point cloud data to remove noise. At the same time, the octree downsampling method is used to simplify the blisk point cloud data, which is beneficial to speed up the subsequent point cloud segmentation efficiency. The PointNet++ model is used to train labeled data to accurately extract blisk point cloud data. The experimental results show that the method can effectively segment the effective information of the whole blisk point cloud model, and the segmentation accuracy reaches 97.4893%.

关键词： Point cloud compression Solid modeling Three-dimensional displays filtering Octrees Noise reduction filtering algorithms

来源：评论

学校读者我要写书评

暂无评论

Robust Widely Nonlinear Quaternion Volterra Adaptive Filter Based on Recursive General Barron Algorithm and its Performance Analysis

引用

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2024年第7期71卷 3578-3582页

作者： Liu, Qianqian Yan, Han Jiangsu Univ Technol Sch Elect & Informat Engn Changzhou 213001 Peoples R China NYU Tandon Sch Engn Brooklyn NY 11201 USA

Recent developments in signal processing have led to the introduction of a novel set of algorithms known as the quaternion-valued second-order Volterra (QSOV) least mean square family, alongside an advanced algorithm termed the widely nonlinear QSOV recursive least square (WNL-QSOV-RLS). These innovative methods are adept at handling signals in 3D and 4D dimensions. Nonetheless, their effectiveness is often challenged in real-world conditions where the error sensor is subjected to impulsive or non-Gaussian noise. Under these circumstances, algorithms relying on the MSE criterion tend to underperform or even diverge. In response to these limitations, this brief introduces the General Barron cost function (GBF), leading to the creation of a novel adaptive filter - the widely nonlinear quaternion-valued second-order Volterra adaptive filter based on recursive GBF (WNL-QSOV-RGBF) algorithm. This brief includes an extensive steady-state analysis of the WNL-QSOV-RGBF algorithm. Furthermore, the efficacy of this newly proposed algorithm, along with its family, is rigorously evaluated through simulation-based system identification and wind prediction tests. These tests unequivocally demonstrate the superior performance of the WNL-QSOV-RGBF algorithm in environments plagued by impulsive noise, compared to existing methods. Complementary to the theoretical analysis, this brief also presents a corroborative simulation study to validate the performance metrics.

关键词： Signal processing algorithms Quaternions Prediction algorithms Steady-state Cost function Adaptive filters filtering algorithms Nonlinear graph filter general robust cost function graph signal processing general Barron

来源：评论

学校读者我要写书评

暂无评论

Singular Value Decomposition Optimizes Multi-Level Orthogonal Code Index Modulation DCSK System

引用

IEEE COMMUNICATIONS LETTERS 2024年第12期28卷 2874-2878页

作者： Zhang, Gang Chen, Xibiao Hu, Yanan Chongqing Univ Posts & Telecommun Sch Commun & Informat Engn Chongqing 400065 Peoples R China

To improve the bit error rate (BER) performance of the differential chaotic shift keying (DCSK) system, this letter proposes a multi-level orthogonal code index modulation DCSK (MOCIM-DCSK) system. A set of mutually orthogonal reference signals is generated using the Gram-Schmidt algorithm, with each reference signal carrying code index bits and modulation bits for the transmission of information signals. Additionally, to further enhance the system's reliability, singular value decomposition (SVD)-aided detection is introduced, successfully suppressing additive white Gaussian noise (AWGN). The BER formulas of MOCIM-DCSK system over AWGN channel and multipath Rayleigh fading channels is derived, and the complexity of MOCIM-DCSK system is compared with other systems. Simulation results validate the correctness of the theoretical derivations and demonstrate the outstanding BER performance of the system. Furthermore, the application of SVD to the MC-DCSK system provides additional evidence of its advantages and versatility in enhancing BER performance.

关键词： Indexes Codes Modulation Matched filters Bit error rate Chaotic communication Receivers filtering algorithms Information filters Spectral efficiency Differential chaos shift keying (DCSK) Gram-Schmidt algorithm code index modulation singular value decomposition

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：