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Precise motion compensation based on weighted sub-pixel image matching (EI CONFERENCE) 会议论文
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, May 24, 2011 - May 26, 2011, Beijing, China
Liang H. G.
收藏  |  浏览/下载:18/0  |  提交时间:2013/03/25
This paper proposed a sub-pixel image correlation algorithm that can get more Precise result  its principle is apply the distribute of relativity peak to get weighted multi-pixel comprehensive of location. Image correlation be as to calculates the greyscale relativity of image template and matching image  the relativity of correspond location where match best with template will be most high  and in its neighbour range  the relativity will be still keep high too. We used these pixel in this local area of calculated match point to get sub-pixel accuracy  the relativity of every pixel be used as its weight for participate the sub-pixel calculation. The sub-pixel location is more accuracy than the integer one  we applied this method to perform background compensation in processing the target detecting for video image sequence. At the end of this paper  some experiment data be proposed  it proved this sub-pixel image correlation can obtain better result. 2011 SPIE.  
Design of GPS/INS integrated navigation system based on multisensor information fusion (EI CONFERENCE) 会议论文
6th World Congress on Intelligent Control and Automation, WCICA 2006, June 21, 2006 - June 23, 2006, Dalian, China
Chunmei H.; Yantao T.; Wanxin S.; Mao L.
收藏  |  浏览/下载:23/0  |  提交时间:2013/03/25
Two kinds of design methods of GPS/INS integrated navigation system are presented  that is GPS/INS integrative system and integrated navigation system based on information fusion. By analyzing mathematics model of the first system error  we found that inertia velocity error would cause code loop track error. Consequently  the pseudo range meterage error is interrelated with inertia velocity error  which is complex to calculate. If this relativity is ignored in the state equation and observation equation of this system  it must affect the estimated precision of the kalman filter and maybe the system is unstable. Therefore  the second integrated navigation method is introduced. It adopts information fusion  federal kalman filter and covariance. And consider the above pertinence to analyze the navigation performance of the integration system. Then it gives the flow of federal kalman filter algorithm. By analyzing  the conclusion is that velocity error of integrated navigation system drops from 0.5m/s to below 0.05m/s  and improves the precision and reliability of the navigation system effectively  well continuity and real-time capability. It provides an effective way for data analysis and process of fusion navigation system. 2006 IEEE.  


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