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检索条件"机构=Science and Technology on Complex Aviation Systems Simulation Laboratory"

共 264 条记录，以下是51-60 订阅

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Satellite Interference Signal Classification Using Improved MLP Model

Satellite Interference Signal Classification Using Improved ...

引用

2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Xie, Liwei Zhuang, Yaqiang Zhuang, Xuebin Zeng, Xiaohui School of Systems Science and Engineering Sun Yat-Sen University Guangzhou China School of Integrated Circuits and Electronics Beijing Institute of Technology Beijing Key Laboratory of Millimeter Wave and Terahertz Technology Beijing China Science and Technology On Complex Aviation Systems Simulation Laboratory Beijing China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

In response to the existing style of deceptive jamming of Global Position System (GPS) receivers by aerial jammer carriers, a method using improved multi-layer perceptron (MLP) model is proposed to identify and classify interference sources based on the rate of change of satellite incoming angle. The work firstly constructs an airborne GPS interference source localization deployment model, then analyzes and verifies the rationality of this simulation data model, and finally emphasizes the superiority of the proposed method using the classical classification algorithm as a comparison method. The simulation results indicated that the proposed method is capable to identify the corresponding interferers with a greater rate of recognition compared with other method in the built multi-interference source environment, which provides a reference for dealing with the interference identification and classification in the networked GPS interference source deployment environment. © 2022 IEEE.

关键词： Antennas

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A new multi-position calibration method for accelerometers of the inertial navigation system 27

A new multi-position calibration method for accelerometers o...

引用

27th Chinese Control and Decision Conference, CCDC 2015

作者： Chan, Li Yuan, Cao Zhang, Shi-Feng College of Aerospace Science and Engineering National University of Defense Technology Changsha China Science and Technology on Complex Land Systems Simulation Laboratory Beijing China

ISBN: (纸本)9781479970179

To guarantee success of precision navigation, it is necessary to carry out in-field calibration for the accelerometers of the inertial navigation system (INS) before a mission is launched. Traditional multi-position calibration method for accelerometers of the inertial measurement units (IMU) are carried out through a turntable (Strap-down INS) or the gimbals(platform INS). To achieve high precision calibration results, the position of the turntable (gimbals) need to be locked precisely. However, the high precision positions are difficult to be attained outside the laboratory. Focusing on this problem, a new calibration method is proposed which uses the gravity residual to reduce the effects caused by locking errors of the positions. simulations are conducted to analyze the performance and the sensitivity of the proposed methods. It is proved that the proposed methods can estimate the accelerometer parameter more precisely than traditional multi-position methods. © 2015 IEEE.

关键词： accelerometers gravity residual INS multi-position

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An Improved PC-Kriging Method for Efficient Robust Design Optimization

An Improved PC-Kriging Method for Efficient Robust Design Op...

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作者： Lin, Qizhang Chen, Chao Xiong, Fenfen Chen, Shishi Wang, Fenggang School of Aerospace Engineering Beijing Institute of Technology Beijing100081 China Science and Technology on Complex Aviation Systems Simulation Laboratory Beijing100076 China Beijing Electromechanical Engineering Institute Beijing100074 China

The polynomial-chaos-kriging (PC-Kriging) method has been derived as a new uncertainty propagation approach and widely used for robust design optimization in a straightforward manner, of which the statistical moments would be estimated through directly conducting Monte Carlo simulation (MCS) on the PC-Kriging model. However, the computational cost still cannot be negligible because thousands of statistical moment estimations might be performed during robust optimization, especially for highly nonlinear and complicated engineering problems. An analytical statistical moment estimation method is derived for PC-Kriging in this work to reduce the computational cost rather than referring to MCS. Meanwhile, a sequential sampling strategy is applied for PC-Kriging model construction, in which the sample points are not generated all at once, but sequentially allocated in the region with the largest prediction uncertainty to improve the accuracy of PC-Kriging model as much as possible. Through testing on three mathematical examples and an airfoil robust optimization design problem, it is noticed that the improved PC-Kriging method with analytical statistical moment estimation and sequential sampling strategy is more efficient than the traditional ones, demonstrating its effectiveness and advantage. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Kriging

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Query modeling for click data based image recognition using graph based propagation and sparse coding

Query modeling for click data based image recognition using ...

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9th International Conference on Internet Multimedia Computing and Service, ICIMCS 2017

作者： Wu, Weichen Tan, Min Zheng, Guangjian Yu, Jun Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China

ISBN: (纸本)9789811085291

We address the fine-grained image recognition problem using user click data, wherein each image is represented as a semantical query-click feature vector. Usually, the query set obtained from search engines is large-scale and redundant. We propose a novel query modeling approach to merge semantically similar queries and construct a compact click feature. We represent each query as a click feature, and design a graph based propagation approach to predict the zero-clicks, ensuring similar images have similar clicks. Afterwards, using this feature, we formulate the problem as a sparse coding based recognition task, wherein the dictionary is discriminatively trained. We evaluate our method for fine-grained image recognition on the public Clickture-Dog dataset. It is shown that, the propagated click feature performs much better than the original one. Also, sparse coding performs better than K-means in query merging. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Image recognition

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Machine Learning Security Analysis Framework Based on Threat Matrix 8

Machine Learning Security Analysis Framework Based on Threat...

引用

8th International Conference on Data science in Cyberspace, DSC 2023

作者： Li, Hu Ma, Qiongmin Zhang, Ming Kuang, Xiaohui National Key Laboratory of Science and Technology on Information System Security Beijing China National Key Laboratory for Complex Systems Simulation Beijing China

ISBN: (纸本)9798350331035

Machine Learning and Artificial Intelligence technology accelerates technological progress and promotes social development, but also brings many security problems. Machine learning models may be affected, deceived, controlled or destroyed at different stages, e.g. training and inference, which may lead to serious consequences. In view of the main stages of the life cycle of machine learning, we summarizes the related attack and defense technologies based on threat matrix, makes a comprehensive and systematic analysis on the security issues of machine learning, and puts forward several security protection suggestions for intelligent information systems. © 2023 IEEE.

关键词： Artificial Intelligence Machine Learning Security Analysis Threat Matrix

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Radar Signal Detection Based on Ambiguity Function and Deep Learning 2

Radar Signal Detection Based on Ambiguity Function and Deep ...

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2nd International Conference on Computer Engineering and Application, ICCEA 2021

作者： Lv, Fengrong Dong, Zeyu Wan, Tao Jiang, Kaili Fang, Xueli Zhang, Lei University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu China Key Laboratory of Complex Aviation Simulation System Beijing China

ISBN: (纸本)9781665426169

The ambiguity function describes the joint characteristics of the signal in the time domain and the frequency domain, and is usually used for signal recognition. The time domain and frequency domain distribution of noise is more spurious than the signal. Its ambiguity function can also reflect its characteristics. However, the direct use of the ambiguity function as the signal feature will increase the amount of calculation of the detection system, so slice it, which reduces the burden on the system for detecting signal information while preserving the information. At the same time, the radar signal detection based on neural network can avoid the influence of artificially setting the threshold on the detection performance of the system. So, we propose an algorithm for inputting the extracted fuzzy function slice sequence into a neural network to realize signal detection. simulation proves that when the signal-To-noise ratio of the received signal is very low, our proposed method still has a high detection probability. © 2021 IEEE.

关键词： Signal detection

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Semi-supervised Open-set Recognition of Radar Active Jamming

Semi-supervised Open-set Recognition of Radar Active Jamming

引用

2021 CIE International Conference on Radar, Radar 2021

作者： Li, Hao Fang, Xueli Zhang, Lei Kang, Hui Zhang, Wei School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China Key Laboratory of Complex Aviation Simulation System Beijing China

ISBN: (纸本)9781665498142

With the emergence of various kinds of complex radar jamming, radar jamming intelligent recognition technology has increasingly become the key to electronic counter-counter measures. To achieve radar jamming open-set recognition with a small number of tagged samples, Generative adversarial network-based pseudolabeled convolutional neural network (GAN-PL-CNN) model is proposed in this paper. Firstly, radar jamming is modelled, and the radar jamming datasets with known and unknown types are established after time-frequency transformation and image processing. Then, the adaptive pseudolabeling method is used to achieve semi-supervised recognition of radar jamming by combining the learning capability of convolutional neural networks and the characteristics of pseudolabeling to increase labeled samples intelligently. Finally, generative adversarial networks are introduced to enhance the recognition ability of the model and the discrimination ability of the unknown type through the game between the generator and the discriminator in the iterative process. Experimental results show that the GAN-PL-CNN model achieves 89.7%-95.1% for known types and 30.7%-86.8% for unknown types at 3%-6% labeling rate. As the number of labeled samples increases, the recognition effect becomes better and has a greater ability to exclude unknown type. © 2021 IEEE.

关键词： convolutional neural network open-set recognition pseudo-label Radar active jamming

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Statistic inference for inertial instrumentation error model using Bayesian network

引用

5th International Conference on Mechanical and Electrical technology, ICMET 2013

作者： Hu, Zheng Dong Zhang, Liu Xin Zhou, Fei Yue Li, Zhi Jun Science and Technology on Complex Land Systems Simulation Laboratory Beijing China Southwest Computer Co. Ltd Chongqing China

ISBN: (纸本)9783037858349

For the parameter estimation problem of inertial instrumentation error models, a Bayesian network is founded to fuse the calibration data and make error coefficients statistical inference in this paper. First the fundamental of Bayesian network is stated and then how to establish network for a typical case of inertial instrumentation error coefficients estimation is illustrated. Since the difficult high-dimension integral calculus for model parameter can be avoidable, WinBUGS software based on MCMC method is used for calculation and inference. The simulated results show that using Bayesian network to make statistical inference for inertial instrumentation error model is reasonable and effective. © (2013) Trans Tech Publications, Switzerland.

关键词： Bayesian networks

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Radar Signal Modulation Recognition Based on Bispectrum Features and Deep learning 2

Radar Signal Modulation Recognition Based on Bispectrum Feat...

引用

2nd International Conference on Computer Engineering and Application, ICCEA 2021

作者： Dong, Zeyu Lv, Fengrong Wan, Tao Jiang, Kaili Fang, Xueli Zhang, Lei University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu China Key Laboratory of Complex Aviation Simulation System Beijing China

ISBN: (纸本)9781665426169

Signal bispectral transformation can not only suppress the influence of Gaussian white noise on signal modulation recognition, but also retain the signal amplitude and phase information. It is also used to extract the non-linear characteristics. Compared with other high-order spectra, bispectrum has a simple processing flow. However, the direct use of all bispectrum as signal features will lead to two-dimensional template matching, causing lots of calculations. Converting two-dimensional bispectrum into one-dimensional sequence, for example, extracting slice information of bispectrum, or using integral bispectrum apparently reduce the amount of data to be processed while retaining part of the bispectrum information. We input the extracted bispectral transformation of radar signals into the neural network to realize modulation recognition. The simulations validate our conclusions that our proposed methods still have a high recognition probability while SNR is low. © 2021 IEEE.

关键词： Template matching

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Using density peaks sentence clustering for update summary generation

Using density peaks sentence clustering for update summary g...

引用

2016 IEEE Canadian Conference on Electrical and Computer Engineering, CCECE 2016

作者： Wu, Guohua Guo, Yutian Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education School of Computer Science and Technology Hangzhou Dianzi University China

ISBN: (纸本)9781467387217

Update summarization can be a daunting task in automatic text summarization. It aims to distill evolved messages from a collection of new articles, under the assumption that the reader has already browsed the previous articles. In this paper, a number of state-of-the-art approaches were reviewed for extracting update summarization and then a method called DPC-TS was proposed. This approach is derived from the DPC-based multi-documents summarization method, which was developed in 2015. In our study, a model was established by using the topic signature algorithm, to evaluate the novelty of sentences in update documents set. In addition, the scheme of calculating similarities between sentences and sentence selection approach was improved to ensure there are diversity topics in the summary. DPC-TS update documents summarization method is a simple and effective approach, which can be reproduced and deployed in real environment. © 2016 IEEE.

关键词： update summarization DPC topic signature dedicated physical channel signature algorithm Novelty Adjudication peaks

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