中国科学院机构知识库网格系统: 检索

Reentry guidance based on feedback linearization (EI CONFERENCE) 会议论文 OAI收割
2011 International Conference on Electronics, Communications and Control, ICECC 2011, September 9, 2011 - September 11, 2011, Ningbo, China
Li D.-W.

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This paper presents a new reentry guidance algorithm for RLV (Reusable Launching Vehicle). The algorithm consists of two integrated components: trajectory planning algorithm and tracking algorithm. The most striking feature of algorithm here lies in that both planning and tracking are executed directly in height-velocity space which is different from the methodology of configuration of drag in traditional shuttle guidance. In the session of trajectory planning all trajectory constraints can be expressed with upper bound and lower bound in height-velocity space then a linear interpolation is carried to search the nominal trajectory satisfying the requirement of downrange and target constraints. Then the tracking algorithm uses feedback linearization method to track this nominal profile and meet all constraints. Another typical feature of this algorithm is the strategy of downrange extension using FPA (flight path angle) controller to fulfill the requirement of large downrange. Proper combination of planning-tracking algorithm and FPA controller can bring great flexibility and adaptability to reentry guidance. The algorithm is proved to be robust enough to accommodate the model error and noises in the dynamics. 2011 IEEE.

The new approach for infrared target tracking based on the particle filter algorithm (EI CONFERENCE) 会议论文 OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China
作者: Sun H.; Han H.-X.; Sun H.

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Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring precision and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure but in order to capture the change of the state space it need a certain amount of particles to ensure samples is enough and this number will increase in accompany with dimension and increase exponentially this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining" we expand the classic Mean Shift tracking framework.Based on the previous perspective we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy to further improve tracking performance. Experimental results show that this algorithm can compensate shortcoming of the particle filter has too much computation and can effectively overcome the fault that mean shift is easy to fall into local extreme value instead of global maximum value.Last because of the gray and fusion target motion information this approach also inhibit interference from the background ultimately improve the stability and the real-time of the target track. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

Evaluation of the operating range for ground-based infrared imaging tracking system (EI CONFERENCE) 会议论文 OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China
作者: Zhang Z.-D.

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Ground-based infrared imaging tracking system (GIITS) is of great importance for aerial target warning and guard. The operating range is one of the key performance specifications on the other which should be calculated calculate the radiation power received on the detector in order to analysis whether the output signal meets the detection requirements or not analyzed and studied during the whole GIITS design process. The operating range is mostly influenced by a few factors without considering the effect of the background radiation. By improving of the traditional method including atmospheric attenuation a new operating range calculation model of the GIITS was established based on two requirements. One is that the image size of observed target should meet the requirement of the processor signal extraction. The number of the pixel occupied by target image should be more than 9. The other is that the signal noise ratio (SNR) of the GIITS should not be less than 5 to meet the requirements of the target detection probability and spatial frequency. The SNR calculation equation in form of energy is deduced and the radiation characteristic of the observed target and background are analyzed. When evaluate the operating range of the GIITS using the new method the performance of GIITS and feature of target and background. This paper firstly makes analysis and summarization on the definite localizations of the traditional operating range equation of the GIITS. The localizations are mainly in two aspects. On one hand we should successively calculate two operating range values according to two requirements mentioned above and choose the minimum value as the analytic result. In the end the dispersion of the image and the effect of image dispersion are not considered in the traditional method an evaluation of operating range for fighter aircraft is accomplished as an example. The influence factors in every aspect on operating range were explored by the calculated result. The new operating range calculation model provides the theoretical basis for the design and applications as well as the comprehensive evaluation of a GIITS. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

TextureGrow: Object recognition and segmentation with limit prior knowledge (EI CONFERENCE) 会议论文 OAI收割
2011 International Conference on Network Computing and Information Security, NCIS 2011, May 14, 2011 - May 15, 2011, Guilin, Guangxi, China
Yao Z.; Han Q.

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In this paper we present a new method for automatically visual recognition and semantic segmentation of photographs. Our automatically and rapidly approach based on Cellular Automation. Most of the analysis and description of recognition and segmentation are based on statistical or structural properties of this attribute most of them need plenty of samples and prior Knowledge. In this paper within a few evident samples (not too many) we can first get the texture feature of each component and the structures then select the approximately location randomly of the objects or patches of them then we use the Cellular Automata algorithm to "grow" based on texture of different objects. The grow progress will stop When texture grow to the boundary. By this steps a new method is found which allow us use very few samples and low lever experience and get a rapidly and accuracy way to recognize and segment objects. We found that this new propose gives competitive results with limited experience and samples. 2011 IEEE.

Computer simulation research on cognitive mechanism of human vision (EI CONFERENCE) 会议论文 OAI收割
International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2010, March 13, 2010 - March 14, 2010, Changsha, China
Ke H.; You W.

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The development of intelligent system which accorded with human cognitive mechanism will exert a profound influence on national defense economy education culture and etc. A computer simulation method according with cognitive mechanism of human vision was proposed on the basis of Structural Decomposition Theory. Many basic shape feature information tables of similar object from different side can determine a kind of object uniquely. System weighted basic shape features in two different information tables by membership degree and then calculated similarity. The identifying object which had the maximum similarity with it in system was what we needed. The system used 83 pictures of 6 kinds of objects with different side for training and testing. The experiment results demonstrated task of basic shape extraction object recognition and others can be completed effectively with the method in paper. The method in paper can be a new attempt on computer simulation method according with cognitive mechanism of human vision from cognitive field. 2010 Crown Copyright.

Quaternion based assessment method for color image fusion algorithms (EI CONFERENCE) 会议论文 OAI收割
2010 3rd International Congress on Image and Signal Processing, CISP 2010, October 16, 2010 - October 18, 2010, Yantai, China
作者: Wang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Y.

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A new approach to assess the performance of color image fusion algorithms is proposed. The color information is fully used by this method. Quaternions are used to encode the pixels in a color image into a quaternion matrix. Local variance of the luminance layer of the color image is taken as the real part of a quaternion then the three RGB channels of the color image are encoded into the three imaginary parts of a quaternion. The angle between the singular value feature vectors of the quaternion matrices corresponding to one of the source image and the fused image is used to measure their structural similarity. Edge information transferring is used to balance the sensitivity of the assessment methods. Experimental results show that the proposed assessment method is better consistent with the HVS than some of the state-of-the-art method. Accurate assessment results can be given by the proposed method for various of color image fusion algorithms by using the source images and the fused image. 2010 IEEE.

A local feature based simplification method for animated mesh sequence (EI CONFERENCE) 会议论文 OAI收割
2010 2nd International Conference on Computer Engineering and Technology, ICCET 2010, April 16, 2010 - April 18, 2010, Chengdu, China
作者: Wang B.; Wang B.; Zhao J.; Zhang S.

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Although animated meshes are frequently used in numerous domains only few works have been proposed until now for simplifying such data. In this paper we propose a new method for generating progressive animated models based on local feature analysis and deformation area preservation. We propose the use of solid angle and height value for a non-hyperbolic vertex to define the local feature parameter. This local factor is embedded to the vertex quadric error matrix when calculating the edge collapse cost. In order to preserve the areas with large deformation we add deformation degree weight to the aggregated quadric errors when computing the unified edge contraction sequence. Finally a mesh optimization process is proposed to further reduce the geometric distortion for each frame. Our approach is fast easy to implement and as a result good quality dynamic approximations with well-preserved fine details can be generated at any given frame. 2010 IEEE.

New features of the Moon revealed and identified by CLTM-s01 期刊论文 OAI收割
SCIENCE IN CHINA SERIES G-PHYSICS MECHANICS & ASTRONOMY, 2009, 卷号: 52, 期号: 12, 页码: 1815-1823
作者: Huang Qian; Ping JinSong; Su XiaoLi; Shu Rong; Tang GeShi

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Chang'E-1 laser altimeter lunar topography dichotomy new feature

Using bidirectional binary particle swarm optimization for feature selection in feature-level fusion recognition system (EI CONFERENCE) 会议论文 OAI收割
2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009, May 25, 2009 - May 27, 2009, Xi'an, China
作者: Wang D.

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In feature-level fusion recognition system the other is optimizing system sensor design to get outstanding cost performance. So feature selection become usually necessary to reduce dimensionality of the combination of multi-sensor features and improve system performance in system design. In general there are two main missions. One is improving the recognition correct rate as soon as possible the optimization is usually applied to feature selection because of its computational feasibility and validity. For further improving recognition accuracy and reducing selected feature dimensions this paper presents a more rational and accurate optimization Bidirectional Binary Particle Swarm Optimization (BBPSO) algorithm for feature selection in feature-level fusion target recognition system. In addition we introduce a new evaluating function as criterion function in BBPSO feature selection method. At the last we utilized Leave-One-Out method to validate the proposed method. The experiment results show that the proposed algorithm improves classification accuracy by two percentage points while the selected feature dimensions are less one dimension than original Particle Swarm Optimization approach with 16 original feature dimensions. 2009 IEEE.

Assessment of color image fusion algorithms based on quaternion singular value decomposition (EI CONFERENCE) 会议论文 OAI收割
MIPPR 2009 - Remote Sensing and GIS Data Processing and Other Applications: 6th International Symposium on Multispectral Image Processing and Pattern Recognition, October 30, 2009 - November 1, 2009, Yichang, China
作者: Wang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Y.

收藏 | 浏览/下载：23/0 | 提交时间：2013/03/25

In this paper a new approach to objectively assess the performance of image fusion algorithms is proposed. It is based on the quaternion representation for the structural information of color images. Quaternions are used to encode the pixels of a color image into a quaternion matrix. Local variance of the luminance layer of color image is taken as the real part of a quaternion then the three RGB channels of the color image are encoded into the three imaginary parts of the quaternion. The angle between the singular value feature vectors of the quaternion matrices corresponding to the source image and the fused image is used to measure the structural similarity of them. Different weight is given to the source images by using variance. The experiment results show that the proposed assessment method is consistent with the HVS. The color information of a color image can be fully used by this method. It can give an accurate assessment result for each fusion algorithm by using the source images and the fused image. 2009 Copyright SPIE - The International Society for Optical Engineering.