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IEEE International Conference on radar

作者： Jinhui Dai Xiuci Mo Wenqiang Pu Junkun Yan Penghui Wang Hongwei Liu National Laboratory of Radar Signal Processing Xidian University Xi'an China Leihua Electronic Technology Research Institution Aviation Industry Corporation of China Wuxi China Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen China

ISBN: (纸本)9781665468893

A joint beam selection and power allocation (JBSPA) scheme is proposed for multiple target tracking (MTT) in active and passive radar network. The motivation of JBSPA is to exploit not only the degrees of freedom of power for active radars but also the degrees of freedom of receive beams for passive radars, thereby improving the overall tracking accuracy of multiple targets. The predictive Posterior Cramér-Rao lower bound is utilized to evaluate the impact of each allocation strategy on tracking performance, and then the JBSPA scheme is formulated as a mixed integer nonlinear program problem. To solve the formulation efficiently, an alternating direction method of multipliers is developed for an optimum. Numerical results demonstrate that the JBSPA scheme can achieve a significant improvement of the overall MTT accuracy, compared with conventional uniform allocation.

关键词： Passive radar Target tracking radar tracking Resource management Optimization

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Aiding AUV Localization Using a Dual-Sided Synthetic Aperture Sonar

Aiding AUV Localization Using a Dual-Sided Synthetic Apertur...

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IEEE International Conference on radar

作者： Shiping Chen Cheng Chi Pengfei Zhang Peng Wang Yu Li Jiyuan Liu Haining Huang Chinese Academy of Sciences Key Laboratory of Science and Technology on Advanced Underwater Acoustic Signal Processing Institute of Acoustics Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665468893

Autonomous underwater vehicle (AUV) navigation and localization is crucial and challenging in Global Positioning System-denied environments. AUV carrying synthetic aperture sonars (SASs) can provide precise motion estimation of the platforms. This study focuses on enhancing the performance of AUV localization using dual-sided SASs. The two-dimensional velocities of AUV are estimated using dual-sided SAS echoes. An extended Kalman filter (EKF) is then adopted for dead reckoning using the estimated velocities. The experimental results demonstrate that the proposed method has better localization accuracy than that of the Doppler velocity log (DVL).

关键词： Location awareness Dead reckoning Delay effects Motion estimation Estimation radar Delay estimation

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A review of dielectric optical metasurfaces for spatial differentiation and edge detection

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Frontiers of Optoelectronics 2021年第2期14卷 187-200页

作者： Lei WAN Danping PAN Tianhua FENG Weiping LIU Alexander A.POTAPOV Department of Electronic Engineering College of Information Science and TechnologyJinan UniversityGuangzhou 510632China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan 430074China JNU-IREE RAS Joint Laboratory of Information Techniques and Fractal Signal Processing Jinan UniversityGuangzhou 510632China Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Education Institutes Jinan UniversityGuangzhou 510632China Institute of Radio Engineering and Electronics Russian Academy of SciencesMoscow 125009Russia

Dielectric metasurfaces-based planar optical spatial differentiator and edge detection have recently been proposed to play an important role in the parallel and fast image processing *** the development of dielectric metasurfaces of different geometries and resonance mechanisms,diverse on-chip spatial differentiators have been proposed by tailoring the dispersion characteristics of subwavelength *** review focuses on the basic principles and characteristic parameters of dielectric metasurfaces as first-and second-order spatial differentiators realized via the Green's function *** spatial bandwidth and polarization dependence are emphasized as key properties by comparing the optical transfer flinctions of metasurfaces for different incident wavevectors and *** present the operational capabilities of a two-dimensional spatial differentiator in image information acquisition,edge detection is described to illustrate the practicability of the *** an application example,experimental demonstrations of edge detection for different biological cells and a flower mold are discussed,in which a spatial differentiator and objective lens or camera are integrated in three optical pathway *** realization of spatial differentiators and edge detection with dielectric metasurfaces provides new opportunities for ultrafast information identification in biological imaging and machine vision.

关键词： dielectric metasurfaces spatial differentiator edge detection optical transfer function

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Fast Coherent point drift

arXiv

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arXiv 2020年

作者： Feng, Xiang-Wei Feng, Da-Zheng Zhu, Yun National Laboratory of Radar Signal Processing Xidian University Xi’an China School of Computer Science Shaanxi Normal University Xi’an China

Nonrigid point set registration is widely applied in the tasks of computer vision and pattern recognition. Coherent point drift (CPD) is a classical method for nonrigid point set registration. However, to solve spatial transformation functions, CPD has to compute inversion of a M x M matrix per iteration with time complexity O (M 3). By introducing a simple corresponding constraint, we develop a fast implementation of CPD. The most advantage of our method is to avoid matrix-inverse operation. Before the iteration begins, our method requires to take eigenvalue decomposition of a M x M matrix once. After iteration begins, our method only needs to update a diagonal matrix with linear computational complexity, and perform matrix multiplication operation with time complexity approximately O (M 2)in each iteration. Besides, our method can be further accelerated by the low-rank matrix approximation. Experimental results in 3D point cloud data show that our method can significantly reduce computation burden of the registration process, and keep comparable performance with CPD on accuracy. Copyright © 2020, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

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A Robust Matching Method for Optical and SAR Images Based on Coarse-to-Fine Mechanism

A Robust Matching Method for Optical and SAR Images Based on...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Cong Li Shuxuan Chen Kun Sun Yi Liang National Laboratory of Radar Signal Processing Xidian University Xi'an China National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing Aerospace Automatic Control Institute Beijing China

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

Although image matching techniques have been developed in the last decades, automatic optical-synthetic aperture radar (SAR) image matching is still a challenging task due to significant nonlinear intensity differences between such images. In this paper, a new method of coarse-to-fine heterogeneous image matching based on contour features is proposed. After images preprocessing, a Canny operator is used to extract open-loop contour features, and the angle feature of local feature points is used to complete coarse matching. Finally, constructing contour tree descriptors of coarse matching pairs, and calculating the contour distance is proposed to obtain the fine matching result. The experimental results show the effectiveness and robustness of this method.

关键词： radar polarimetry Optical imaging Adaptive optics Feature extraction Optical reflection Nonlinear optics Optical filters

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A Recommender System for Metaheuristic Algorithms for Continuous Optimization Based on Deep Recurrent Neural Networks

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2020年第1期1卷 5-18页

作者： Tian, Ye Peng, Shichen Zhang, Xingyi Rodemann, Tobias Tan, Kay Chen Jin, Yaochu Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Institutes of Physical Science and Information Technology Anhui University Hefei 230601 China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei 230601 China Honda Research Institute Europe Offenbach 63073 Germany Department of Computer Science City University of Hong Kong Kowloon Tong Hong Kong Hong Kong Department of Computer Science University of Surrey Guildford GU2 7XH United Kingdom Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang 110819 China

As revealed by the no free lunch theorem, no single algorithm can outperform any others on all classes of optimization problems. To tackle this issue, methods for recommending an existing algorithm for solving given problems have been proposed. However, existing recommendation methods for continuous optimization suffer from low practicability and transferability, mainly due to the difficulty in extracting features that can effectively describe the problem structure and lack of data for training a recommendation model. This work proposes a generic recommender system to address the above two challenges. First, a novel method is proposed to represent an analytic objective function of a continuous optimization problem as a tree, which is directly used as the features of the problem. For black-box optimization problems whose objective function is unknown, a symbolic regressor is adopted to estimate the tree structure. Second, a large number of benchmark problems are randomly created based on the proposed tree representation, providing an abundant amount of training data with various levels of difficulty. By employing a deep recurrent neural network, a recommendation model is trained to recommend a most suitable metaheuristic algorithm for white- or black-box optimization, making a significant step forward towards fully automated algorithm recommendation for continuous optimization. Experimental results on 100 000 benchmark problems show that the proposed recommendation model achieves considerably better performance than existing ones, and exhibits high transferability to real-world problems. Impact Statement—Real-world optimization problems, such as aerodynamic design of turbine engines and automated trading, have been successfully solved by metaheuristics. However, practitioners are confronted with the challenge of how to choose an appropriate metaheuristic algorithm to solve a particular instance of these problems. This paper proposes a recommender system that can auto

关键词： Algorithm recommendation continuous optimization problem decision tree deep recurrent neural network metaheuristics symbolic regression

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Corrigendum to “Strong convergence theorem of a new modified Bregman extragradient method to solve fixed point problems and variational inequality problems in general reflexive Banach spaces [Communications in Nonlinear science and Numerical Simulation, 135, (2024): CNSNS 108051]

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Communications in Nonlinear science and Numerical Simulation 2024年 138卷

作者： Huilin Tan Qian Yan Gang Cai Qiaoli Dong School of Mathematical Sciences Chongqing Normal University College of Sciences Chongqing University of Technology Tianjin Key Laboratory for Advanced Signal Processing and College of Science Civil Aviation University of China

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Consensus Disturbance Rejection of Nonlinear Multi-Agent Systems Over Cooperation-Competition Networks

Consensus Disturbance Rejection of Nonlinear Multi-Agent Sys...

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Chinese Automation Congress (CAC)

作者： Qiang Wang Wangli He Dayu Tan Weimin Zhong Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781665426480

This study addresses the consensus problem for nonlinear multi-agent systems (MASs) under the exogenous disturbances over cooperation-competition networks. Firstly, for judging the disturbances produced by the exogenous environment, a disturbance observer-based approach is developed and incorporated into the controller. Secondly, two novel nonlinear control protocols depended on state feedback and output feedback control are constructed to guarantee consensus for MASs over the signed directed graph, respectively. Thirdly, theoretical guarantees on the effectiveness of the proposed controller in steering the system to a bipartite leader-following consensus with exogenous disturbances are derived. Finally, numerical simulations inspired by a real-world physical MAS are provided to illustrate the effectiveness of the proposed controllers.

关键词： State feedback Protocols Automation Directed graphs Numerical simulation Disturbance observers Output feedback

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signal Fusion-based Detection with an Intuitive Weighting Method

Signal Fusion-based Detection with an Intuitive Weighting Me...

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IEEE National Conference on radar

作者： Jing Lu Shenghua Zhou Jianlai Wang Dawei Li Tieshan Feng Hongwei Liu Hui Ma National Laboratory of Radar Signal Processing Xi'an China Xidian University Xi'an China China Academy of Launch Vehicle Technology Beijing China

ISBN: (数字)9781728189420

ISBN: (纸本)9781728189437

In a distributed multiple-input multiple-output (MIMO) radar, signal fusion based detection can achieve the best detection performance but the global test may be a complicated combination of local observations, such that a closed-form expression of the false alarm rate may be hard to develop, especially for heterogeneous local observations. In this paper, we study how to impose better linear weights on local test statistics for a global test resulting in a better detection performance. Since the weights of the generalized likelihood ratio test (GLRT) have been proved to be suboptimal, an intuitive and tractable weighting method is presented that weights the local test statistics according to the estimated channel signal-to-noise ratios (SNRs) and the power of the local test statistics measured by the detection probability curve. With a linear combination of local test statistics, the false alarm rates can be computed conveniently. This method is also applicable to heterogeneous local observations. Numerical results for the performance of the distributed cell-averaging constant false alarm rate (CA-CFAR) algorithm and the distributed GLRT algorithm indicate that the proposed weighting method can outperform conventional algorithms.

关键词：

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Knowledge-Aided Direct Data Domain STAP Algorithm for Forward-looking Airborne radar

Knowledge-Aided Direct Data Domain STAP Algorithm for Forwar...

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2019 IEEE International Conference on signal, Information and Data processing, ICSIDP 2019

作者： Gao, Zhiqi Tao, Haihong College of Information Engineering Inner Mongolia University of Technology Hohhot China National Laboratory of Radar Signal Processing Xidian University Xi'an China

ISBN: (纸本)9781728123455

A knowledge-aided direct data domain (D3) algorithm, which is applied to the space-time adaptive processing (STAP), is proposed. The conventional D3 algorithm only uses the test data to avoid heterogeneous training data. However, the prior knowledge of target is always not accurate, leading to performance degradation. The D3 algorithm based on sparse representation suffers target self-nulling and clutter suppression performance degradation. To overcome these disadvantages, a knowledge-aided D3 algorithm is proposed to improve the STAP performance. The prior knowledge about clutter distribution of forward-looking airborne radar is exploited to distinguish clutter components and targets. Furthermore, the clutter components can be eliminated from the sparse recovery coefficient vector. Hence, we can judge if the targets are present via the power of reminder element. Then, the clutter components are exploited to estimate the STAP filter weight, which can supply satisfactory clutter suppression performance. Experiments validate that the proposed algorithm separate the clutter components and targets directly without the prior knowledge of targets, and the target detection performance is improved significantly. © 2019 IEEE.

关键词： Space time adaptive processing

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