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Chinese Automation Congress (CAC)

作者： Xinghai Gao Yaqi Zhang Zhuoqi Wang Institute of Unmanned System Beihang University Beijing China Science and Technology on Complex Systems Simulation Laboratory Beijing China

The rapid increasing challenges of modeling and simulation for systems-of-systems Engineering (SoSE) is to deal with their large-scale and complexity of heterogeneous and inter-dependent constituent systems. Typically, the method of structural modeling provides a thorough understanding of the composition and operation of different elements, but loses sight of the dynamic characteristics of the systems or components. To make a comprehensive analysis of the system-of-systems (SoS), the solution of behavior modeling will be more important to adapt to the evolving of the SoS, which focus on understanding the constituent systems and their relationships, and evaluating changes of the constituent system, and continuously responding to the new requirements and options of SoS. This paper discusses how to support the application of modeling and simulation (M&S) based on the framework of SysML to describe the architecture and capability of SoS, and combined with the process and activities of model-based system engineering (MBSE).

关键词： Unified modeling language Object oriented modeling Analytical models Digital systems Adaptation models

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Denoising of hyperspectral images based on principal component analysis and adaptive sparse coding 10

Denoising of hyperspectral images based on principal compone...

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10th IAPR Workshop on Pattern Recognition in Remote Sensing, PRRS 2018

作者： Xiaorui, Song Lingda, Wu Space Engineering University Science and Technology on Complex Electronic System Simulation Laboratory Beijing101416 China

ISBN: (纸本)9781538684795

In view of the special properties of hyperspectral images(HSI) in the transform domain, in this paper, a new denoising method of HSI based on principal component analysis(PCA) and adaptive sparse coding is proposed. Firstly, the principal component image of each channel is obtained by performing PCA transform on the noisy HSI. Then, the first PCA output channels which contain a majority of the total energy of an HSI data cube are retained, and the rest PCA output channels which contain a small amount of energy, termed noise component images, are subjected to noise reduction through an adaptive sparse coding method. The encoding dictionaries are learned from each channel of noise component images by an approach of online dictionary learning. Finally, the denoised HSI is obtained by the inverse PCA transform. The proposed method takes the advantages of PCA and adaptive sparse representation that has better adaptability to the HSI. It not only performs better in denoising, but also preserves the details and alleviates the blocking artifacts well. The effectiveness of the proposed approach to hyperspectral denoising, termed PCASpC, is illustrated in a series of experiments with synthetic and realworld data where it outperforms the state-of-the-art. © 2018 IEEE.

关键词： Principal component analysis

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Wireless sensor network localization approach based on bayesian MDS 5th

Wireless sensor network localization approach based on bayes...

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5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017

作者： Pei, Zhongmin Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing101416 China

ISBN: (纸本)9789811308956

The aim of wireless sensor networks (WSNs) are to perceive, collect and process the information of sensor nodes within the coverage of the network. As a bridge between the physical world and the digital one, WSNs have widely been applied in many fields. One of the key issues for most applications is to know the location of sensor nodes. Though localization algorithms based on multidimensional scaling (MDS), which only need several anchor nodes, have been proven to be robust with respect to range-based implementations, these methods are sensitive inaccuracy range measure. This article proposes a novel localization algorithm based on Bayesian MDS, named as MDS-MAP(P, B), where P and B denote the use of patching of local maps and Bayesian MDS, respectively. Experimental results in real-world systems show that our method is more robust and efficient. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Sensor nodes

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Visualization of pairwise data: An overview 3

Visualization of pairwise data: An overview

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3rd IEEE International Conference on Data science in Cyberspace, DSC 2018

作者： Pei, Zhong-Min Xiong, Ming-Hui Xiong, Wei Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing101416 China

ISBN: (纸本)9781538642108

It is difficult for some applications to extract feature functions in the process of data visualization. Focus on the problem of large-scale pairwise data visualization, the paper first introduces and analysis the problem. Then the current mainstream methods for pairwise data visualization are analyzed. On the basis of active learning and configuration suture, the paper proposes a fast visualization method. The overall research framework, the key technologies are presented to provide some research ideas and recommendations for pairwise data visualization. © 2018 IEEE.

关键词： Data visualization

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Cooperative collision avoidance method for multi-UAV based on kalman filter and model predictive control

Cooperative collision avoidance method for multi-UAV based o...

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2019 IEEE International Conference on Unmanned systems and Artificial Intelligence, ICUSAI 2019

作者： Huang, Hanqiao Zhou, Huan Zheng, Meiyun Xu, Cheng Zhang, Xiaofeng Xiong, Wei Unmanned System Research Institute Northwest Polytechnical University Xi'an China Aeronautical Engineering College Air Force Engineering University Xi'an China School of Marine Science and Technology Northwest Polytechnical University Xi'an China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China UAV Researc Center Army Aviation Institute Beijing China

ISBN: (纸本)9781728158594

Collision avoidance is the primary problem to be solved in formation flight of multiple Unmanned aerial vehicles(UAVs). Firstly, a cooperative collision avoidance architecture of multiple UAVs is designed according to the requirement of autonomous collision avoidance of single UAV. Then a new cooperative collision avoidance method of multiple UAVs based on Kalman filter and model predictive control(MPC) is proposed. In this method, extended Kalman filter(EKF) is used to estimate the state of obstacles and target points in uncertain environment space, and to predict the trajectory of obstacles and target points. At the same time, relevant performance index functions and constraints are set up. On the basis of sharing environmental information, model predictive control strategy is used to guide and make cooperative collision avoidance decisions for multiple UAVs. The simulation results show that the proposed method is effective in uncertain environment perception and UAV collision avoidance, and the cooperative mechanism has obvious advantages. © 2019 IEEE.

关键词： Model predictive control

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Error Analysis of Object Depth Measurement Method Based on Feature Line Segments

Error Analysis of Object Depth Measurement Method Based on F...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Chuanqi Zhang Yunfeng Cao Meng Ding Donghui Wei College of Astronautic Nanjing University of Aeronautics and Astronautics Nanjing China College of Civil Aviation Nanjing University of Aeronautics and Astronautics Nanjing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (数字)9781728180250

ISBN: (纸本)9781728180267

This paper focuses on the problem of object depth measurement in ultra-low altitude flight, which has always been a research hotspot in the field of machine vision. Compared with the previous object depth measurement method based on a single handcrafted feature point, the method based on feature line segments can effectively weaken the adverse effect caused by the feature matching error. However, since this method involves both image processing algorithms and the use of position data provided by navigation devices, various errors will be introduced. To this end, this paper points out the error sources of that may affect the accuracy of the object depth measurement results under this method. Then, through numerical simulation, the errors are simulated and their influence rules are analyzed, with the qualitative and quantitative results presented. Finally, we also give the allowable value range of each error under the minimum requirement that the object depth measurement error in ultralow altitude flight missions does not exceed 20%, which provides a reference and guidance for both algorithm selection and practical application.

关键词： Feature extraction Atmospheric modeling Pipelines Object segmentation Measurement uncertainty Measurement errors Intelligent agents

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Radial Accelerated Velocity Estimation for Moving Ship Target Imaging based on GRFT in Geosynchronous SAR

Radial Accelerated Velocity Estimation for Moving Ship Targe...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Ying Zhang Wei Xiong Xichao Dong Cheng Hu Chengxiang Liu Yang Sun Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China School of Information and Electronics Beijing Institute of Technology Beijing China

ISBN: (数字)9780996007894

ISBN: (纸本)9781728146331

GEO SAR has great potential in marine surveillance. But the extremely low SNR of echo, resulting in the traditional signal integration method become invalid. This paper proposes an improved GRFT-based approach to realize the moving ship targets' radial accelerated velocity estimation. Firstly, the accurate slant range is constructed which has considered the curved synthetic aperture trajectory. Then, the GRFT-based estimation method is redefined to realize radial accelerated velocity estimation and imaging. Finally, the simulation results are given to verify the proposed methods.

关键词： Acceleration Marine vehicles Synthetic aperture radar Estimation Imaging systems simulation Aerospace electronics

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Range migration-based Doppler ambiguous integer estimation for moving targets with azimuth spectrum aliasing

Range migration-based Doppler ambiguous integer estimation f...

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Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

ISBN: (数字)9781728129129

ISBN: (纸本)9781728129136

In some case, the azimuth spectrum bandwidth is larger than the pulse repetition frequency (PRF), leading to a whole azimuth spectrum has been folded into multiple subsegments and aliased. Therefore, the traditional Doppler ambiguous integer estimation method cannot be used directly. In this paper, the influence of Doppler ambiguous integer on residual range migrations' slope is analyzed. Based on the slope, the Doppler ambiguous integer estimation method for moving targets with azimuth spectrum aliasing is given. From the simulation results, the Doppler ambiguous integer can be estimated accurately by proposed method.

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A Novel Geosynchronous Spaceborne-Airborne Bistatic Multichannel Sar For Ground Moving Targets Indication

A Novel Geosynchronous Spaceborne-Airborne Bistatic Multicha...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Xichao Dong Wei Xiong Ying Zhang Cheng Hu Feifeng Liu School of Information and Electronics Beijing Institute of Technology Beijing China Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China

Geosynchronous synthetic aperture radar (GEO SAR) has great potentials in synthetic aperture radar ground moving target indication (SAR-GMTI) due to its high time resolution and wide swath coverage. But the signal-to-noise ratio (SNR) of echo is too low and multichannel configuration cannot be realize in GEO monostatic SAR. Therefore, geosynchronous spaceborne-airborne bistatic multichannel synthetic aperture radar (GEO-SABM SAR) can realize enhanced SNR and multichannel configuration. In this paper, we establish the slant range model for GEO-SABM SAR and give the VSAR processing flowchart. Finally, the numerical experiments is given to verify the effectiveness of proposed method.

关键词： Synthetic aperture radar Clutter Doppler effect Imaging Flowcharts Orbits Remote sensing

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Better Modeling the Hierarchical Structure of Language for Sentence Semantic Matching

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Journal of Physics: Conference Series 2020年第1期1651卷

作者： Zhongmin Pei Changqun Li Wei Xiong Zhangkai Luo Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing 100014 China

Sentence semantic matching requires understanding the semantic relationship between two sentences, which is widely used in various natural language tasks such as paraphrase identification, natural language inference and question answering. Usually, the underlying structure of sentence is not strictly sequential, this structure is hierarchical. This paper studies how to better model the hierarchical structure of sentence for semantic matching. Recent research suggests that BERT implicitly captures classical, tree-like structures. Based on this, this paper proposes to further enhance the strength of modeling hierarchical structure of language with an advanced variant of LSTM – Ordered Neurons LSTM(ON-LSTM), which introduces a syntax-oriented inductive bias to perform the composition of classical tree structure. Experimental results demonstrate that the proposed approach, which enhances hierarchical structure of language, significantly improves the performance of sentence semantic matching.

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