Chinese Aeronautical Radio Electronics Research Institute

Chinese, China

Chinese Aeronautical Radio Electronics Research Institute

Chinese, China

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Gao J.,Beihang University | Zhang Y.,Chinese Aeronautical Radio Electronics Research Institute
Proceedings - 2013 International Conference on Virtual Reality and Visualization, ICVRV 2013 | Year: 2013

The PnP (perspective-n-point) problem is very important in pose estimation technique based on computer vision. Aiming at this issue, an improved iterative solution is proposed. By the means of expressing the 3D point coordinates as a weighted sum of four control points, a system of homogeneous linear equations was established and then the optimized projections on the normalized image plane were obtained. The final estimation result was achieved by a relaxation-based iterative approach. Both simulations and experiments certify that the proposed algorithm can improve the computing accuracy and depress the image noise. Compared with other solutions to the PnP problem, the proposed algorithm can reduce the computational complexity while maintaining high precision with noise depression capability. © 2013 IEEE.


Pan H.,Beihang University | Zhang Y.,Chinese Aeronautical Radio Electronics Research Institute
Proceedings - 2013 International Conference on Virtual Reality and Visualization, ICVRV 2013 | Year: 2013

Height field and grid data are frequently updated during simulation of large scale ocean water, which reduces the frame rates of whole virtual scene. A CUDA-based framework for unbounded real-time ocean rendering is proposed in this paper. Firstly, height field data is calculated on GPU using FFT method. Then the whole view frustum dependent dynamic grid is created by an adaptive algorithm with continuous LOD, and positions of vertices are updated in CUDA kernels. Finally, normal map is generated using height field data on GPU and blended with perlin noise to shade ocean surface. Data transferred between GPU memory and primary memory is constrained during rendering loop. Experiments show the proposed framework achieves several times of speedup in grid updating efficiency than CPU implementation, and gets realtime and realistic ocean rendering results as well. © 2013 IEEE.


Liu S.,Beihang University | Dai S.,Beihang University | Zhang Y.,Chinese Aeronautical Radio Electronics Research Institute
Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics | Year: 2014

In order to apply high level architecture (HLA) in some real time systems, real-time performance of run-time infrastructure (RTI) must be guaranteed. Because of precedence constraints of correlated tasks between federates, it is hard to provide predictable response for all tasks, and it is also difficult to ensure the real-time performance of all tasks, especially aperiodic ones. The double-earliest deadline first (D-EDF) strategy of how to schedule overall periodic and aperiodic tasks inside a federate was discussed from the point view of task scheduling theory. The policy can not only discard some redundant data to ensure the periodic tasks completed effectively before their deadlines, but also schedule aperiodic ones running regularly to improve their real-time responding speed. It makes the system effectively handle the tasks with precedence constraints and consequently improves the real-time performance of RTI. The feasibility of the D-EDF scheduling strategy was proved.


Niu W.,Northwestern Polytechnical University | Wang G.,Chinese Aeronautical Radio Electronics Research Institute | Zhai Z.,Northwestern Polytechnical University | Cheng J.,Xian Institute of Applied Optics
Applied Mechanics and Materials | Year: 2012

Recently, the dominating difficulty that fault intelligent diagnosis system faces is terrible lack of typical fault samples, which badly prohibits the development of machinery fault intelligent diagnosis. Mainly according to the key problems of support vector machine need to resolve in fault intelligent diagnosis system, this paper makes more systemic and thorough researches in building fault classifiers, parameters optimization of kernel function. A decision directed acyclic graph fault diagnosis classification model based on parameters selected by genetic algorithm is proposed, abbreviated as GDDAG. Finally, GDDAG model is applied to rotor fault system, the testing results demonstrate that this model has very good classification precision and realizes the multi-faults diagnosis. © (2012) Trans Tech Publications, Switzerland.


Niu W.,Northwestern Polytechnical University | Wang G.,Chinese Aeronautical Radio Electronics Research Institute | Zhai Z.,Northwestern Polytechnical University | Cheng J.,CNGC the 205 institute
International Journal of Digital Content Technology and its Applications | Year: 2011

Fault prediction is of great importance to ensuring weapon equipment safety and reliability. Usually the data for fault detection and prediction of weapon equipment have feature like small samples, although the current main fault prediction methods have achieved certain success in practical application, they all fall short in some aspects. For chaos of weapon equipment fault data, based on rough sets and support vector machine modeling theory, an optimal least square support vector machine prediction method is proposed. Firstly, redundant information in time series is removed by rough sets. secondly, time series after reduction is prediction by support vector machine. The data of a certain aeroengine are taken as an example for prediction and analysis, and the results show that the model simplifies complexity of modeling and has high prediction precision, which in turn validates its availability.


Niu W.,Northwestern Polytechnical University | Wang G.,Chinese Aeronautical Radio Electronics Research Institute | Zhai Z.,Northwestern Polytechnical University | Cheng J.,CNGC the 205 institute
Advances in Information Sciences and Service Sciences | Year: 2011

Although the grey forecasting model has been successfully adopted in various fields and demonstrated promising results, the literatures show its performance could be further improved. The paper proves that the growth rate of the simulated value of the GM(1,1) is a fixed value. If the growth rates of the primary sequence are equate, the fitted value deriving from GM(1,1) is the same as the primary sequence, otherwise greater error would occur. In order to overcome shortcoming of the fixed growth rates, GM(1,1) is improved by introducing linear time-varying terms. Using the optimization method, the paper studies the iterative datum. The new model is called improved GM(1,1), abbreviated as IGM(1,1). Meanwhile, by contrasting IGM(1,1) model to the GM(1,1) model, the result shows that IGM(1,1) model has largely improves fitting and predicting precision.


Niu W.,Northwestern Polytechnical University | Cheng J.,CNGC the 205 Institute | Wang G.,Northwestern Polytechnical University | Wang G.,Chinese Aeronautical Radio Electronics Research Institute
Journal of Combinatorial Optimization | Year: 2013

Although the grey forecasting model has been successfully adopted in various fields and demonstrated promising results, the literatures show its performance could be further improved. For this purpose, this paper proves that the growth rate of the simulated value of the grey model GM(1,1) is a fixed value. If the growth rates of the primary sequence are equate, the fitted value deriving from GM(1,1) is the same as the primary sequence, otherwise greater error would occur. In order to overcome shortcoming of the fixed growth rates, extend the traditional GM(1,1) model by introducing linear time-varying terms, which can predict more accurately on non geometric sequences, termed EGM(1,1). Finally, compared with the other improved grey model and ARIMA model, experimental results indicate that the proposed model obviously can improve the prediction accuracy. © 2012 Springer Science+Business Media, LLC.


Hong R.,Chinese Aeronautical Radio Electronics Research Institute | Xiong Z.,Chinese Aeronautical Radio Electronics Research Institute | Zhou Q.,Chinese Aeronautical Radio Electronics Research Institute
AIAA Modeling and Simulation Technologies Conference, 2016 | Year: 2016

This paper is mainly about system verification in model based system engineering. The typical design tools in system engineering as Rhapsody and scenario modeling tool as STK are both introduced and discussed. After analyzing the characteristics of Rhapsody in requirements analysis and functions modeling, and STK in scenario modeling and animation, this paper proposed a method of system simulation and verification in System Engineering. The proposed method starts with scenario modeling in STK and then integrating Rhapsody behavior models to STK scenario models. The proposed method integrates the two kinds of models in system development by interconnection and communication. The scenario models show the requirements in animation which give the users and engineers a more direct way. Rhapsody models take the scenario models as the basis and then simulate the structures and behaviors of the object systems. In this way, the two kinds of models keep consistency at the fisrt step. Then, the scenario models of STK can send events to Rhapsody models during the time of animation. The scenario models of STK sending events as simulator to trigger the statecharts of Rhapsody by causing status transfer in model execution. Meanwhile, Rhapsody models being executed are used as logical supporter to STK scenario models. If the status transfer of Rhapsody statechart showing incorrect, it means the scenario models of STK may be also inappropriate. But it is not easy to find the inappropriateness of scenarios by STK model itself. The proposed way of simulating helps users find the incorrectness in modeling as early as possible. By using this method, the Rhapsody models and the STK models verify each other and promote both the correctness and preciseness of system models effectively. © 2016 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.


Lu J.,Harbin Engineering University | Zhang X.,Harbin Engineering University | Gao L.,Chinese Aeronautical Radio Electronics Research Institute | Dong D.-L.,China National Petroleum Corporation
Guangdianzi Jiguang/Journal of Optoelectronics Laser | Year: 2014

In the coded structured light vision measurement, as a kind of spatial code, color coded structured light has good properties, such as high speed of shape measurement, because it only needs to project one or a few patterns. Coding and decoding are its key problems. The captured color stripe is easily affected by environmental factors, such as light, so the color is often recognized incorrectly. As the number of colors increases, the probability of error becomes bigger. With good measurement resolution, introducing color intensity and period properties and using 4 colors, a color pattern with 128 stripes is designed based on De Bruijn sequences in this paper. The pattern is convenient for subsequently decoding and meeting the requirements of the high measurement resolution at the same time. Color stripes are precisely segmented by means of applying linear filter difference to L channel value in L*a*b* color space. An adaptive color clustering method is designed by employing principal component analysis and K means clustering, which overcomes the difficulty of color identifying caused by the color crosstalk and is able to accurately classify colors of stripes with high or low intensity. Matching points set is produced by using the window's uniqueness of De Bruijn sequences. The 3D information on the surface of the object is obtained according to the principle of triangulation. The 3D object surface is reconstructed finally. This method is used to measure a cylinder diameter. The measurement error is about 1.5 mm. The relevant error is about 0.5%. The effectiveness of the proposed method is validated by the experimental results.


Lv G.,Northwestern Polytechnical University | Hu S.,Chinese Aeronautical Radio Electronics Research Institute | Lu X.,Northwestern Polytechnical University
ICALIP 2014 - 2014 International Conference on Audio, Language and Image Processing, Proceedings | Year: 2015

This paper introduced the semi-continuous Hidden Markov Model (HMM) and proposed a novel Dynamic Bayesian Network (DBN) model for dynamic speech emotion recognition. The former reduces the training complexity caused by mixture Gaussians by sharing the Condition Probability Densities (CPDs) of Gaussians among the states, and the latter adds a sub-state layer between state and observation layer based on traditional DBN framework and describes the dynamic process of speech emotion in detail. Experiments results show that average emotion recognition rate of semi-continuous HMM is 4% and 10% higher than those of classical HMM and Mixture Gaussian HMM respectively, and average emotion recognition rate of the three-layer DBN model is 11% and 8% higher than those of traditional DBN model and semi-continuous HMM. © 2014 IEEE.

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