HU Bing-ua, YAN Hui, WU Heng. Measurement of moving object by multi-source data based on moving platform[J]. Journal of Applied Optics, 2013, 34(4): 619-623.
Citation: HU Bing-ua, YAN Hui, WU Heng. Measurement of moving object by multi-source data based on moving platform[J]. Journal of Applied Optics, 2013, 34(4): 619-623.

Measurement of moving object by multi-source data based on moving platform

More Information
  • An image data measurement system was created based on the moving target performance testing requirements and the characteristics of test platform, in order to realize video recording and external parameters measurement of the target. Multiple highspeed cameras were reasonably arranged from calculated distance of the camera and mimic diagram. Camera calibration method was used which is combined the checkerboardlattice parameter calibration in OpenCV with the linebasis field calibration. Additional, highspeed image data, midline video data and GPS data were combined to achieve the measurement of position, attitude and other external parameters. Analysis of measurement accuracy and experimental results prove that the measurement method is accurate and reliable. Its coordinate accuracy is better than 10 cm in horizontal direction and 5 cm in elevation direction, and the attitude accuracy is better than 05, which fully meet the measurement accuracy requirements..
  • [1]杜俊峰. 光电经纬仪测量精度指标的确定[J]. 应用光学, 2006, 27(6) :506-509.
    DU Jun-feng. Error budget design for photoelectric theodolite[J]. Journal of Applied Optics, 2006, 27(6): 506-509.(in Chinese with an English abstract)
    [2]周剑, 胡建, 任德新,等. 高动态运动目标参数摄像测量方法与系统[J]. 战术导弹技术, 2011 (1) :99-104.
    ZHOU Jian, HU Jian, REN De-xin,et al. Videometric method and system of high-speed objects[J]. Tactical Missile Technology January, 2011 (1):99-104.(in Chinese with an English abstract)
    [3] 王国龙,衣同胜. 靶场光电测量技术应用展望[J]. 光学精密工程, 2003, 11(4) :213-217.
    WANG Guo-long, YI Tong-sheng. Perspective of the application of photoelectric measurement in test range[J]. Optics and Precision Engineering, 2003, 11(4) :213-217.(in Chinese with an English abstract)
    [4]王之卓. 摄影测量原理[M]. 武汉: 武汉大学出版社, 2007.
    WANG Zhi-zhuo. Principles of photogrammetry[M]. Wuhan: Wuhan University Press, 2007.(in Chinese)
    [5]牛海涛, 赵勋杰. 采用棋盘格模板的摄像机标定新方法[J]. 红外与激光工程, 2011, 40(1) :133-137.
    NIU Hai-tao, ZHAO Xun-jie. New method of camera calibration based on checkerboard[J]. Infrared and Laser Engineering, 2011, 40(1) :133-137.(in Chinese with an English abstract)
    [6]田克微, 张爱武, 王少敏. 一种基于OpenCV的摄像机标定方法[J]. 首都师范大学学报:自然科学版, 2008, 29(2):14-17.
    TIAN Ke-wei, ZHANG Ai-wu, WANG Shao-min. A camera calibration method based on openCV[J]. Joumal of Capital Normal University: Natural Science Edition, 2008, 29(2):14-17.(in Chinese with an English abstract)
    [7]张永军. 基于序列图像的视觉检测理论与方法[M]. 武汉: 武汉大学出版社, 2008.
    ZHANG Yong-jun. The theory and method of visual inspection based on image sequence[M]. Wuhan: Wuhan University Press, 2008.(in Chinese)
    [8]张剑清, 潘励, 王树根. 数字摄影测量学[M]. 武汉: 武汉大学出版社, 2006.
    ZHANG Jian-qing, PAN Li, WANG Shu-gen. Digital photogrammetry [M]. Wuhan: Wuhan University Press, 2006.(in Chinese)
    [9]赵彩英, 张兴国. 基于多源信息融合的空中运动目标定位技术[J]. 测控技术, 2012, 31(6): 26-29.
    ZHAO Cai-ying, ZHANG Xing-guo. Technology of moving object determination of spatial positon based on multi-source information fusion[J]. Measurement & Control Technology, 2012, 31(6): 26-29.(in Chinese with an English abstract)
    [9]贾浩正, 罗耀蓉. 单影像运动目标六维参数测量方法[J]. 光电工程, 2010, 37(6) :11-14.
    JIA Hao-zheng, LUO Yao-rong. 6D parameter measurement method for moving objects based on single image[J]. Opto-Electronic Engineering, 2010, 37(6) :11-14.(in Chinese with an English abstract)
  • Related Articles

    [1]ZHOU Kehu, LEI Tao, LUO Gang. Infrared sequence images denoising algorithm based on temporal filtering[J]. Journal of Applied Optics, 2021, 42(3): 474-480. DOI: 10.5768/JAO202142.0302004
    [2]QI Faguo, ZHANG Haiyang, LIU Chun, ZHAO Changming, ZHANG Zilong. Image denoising algorithm based on dual-branch modified codec[J]. Journal of Applied Optics, 2020, 41(5): 956-964. DOI: 10.5768/JAO202041.0502004
    [3]CHEN Qingjiang, SHI Xiaohan, CHAI Yuzhou. Image denoising algorithm based on wavelet transform and convolutional neural network[J]. Journal of Applied Optics, 2020, 41(2): 288-295. DOI: 10.5768/JAO202041.0202001
    [4]CHEN Qingjiang, SHI Xiaohan, CHAI Yuzhou. Image denoising algorithm based on information preservation network[J]. Journal of Applied Optics, 2019, 40(3): 440-446. DOI: 10.5768/JAO201940.0302006
    [5]Wu Haibing, Zhang Liang, Gu Guohua, Tao Haijun, Ning Quanli. Color image enhancement based on LLL tricolor image denoising and fusion[J]. Journal of Applied Optics, 2018, 39(1): 57-63. DOI: 10.5768/JAO201839.0102003
    [6]Fan Ying, Qiu Lirong, Zhao Weiqian, Wang Yun. Wavelet denoising method for step threedimensional shape information[J]. Journal of Applied Optics, 2016, 37(4): 542-548. DOI: 10.5768/JAO201637.0402002
    [7]Lu Bibo, Li Yang, Wang Yongmao. Color image denoising using high order iterating model by combining relaxed median filter[J]. Journal of Applied Optics, 2016, 37(3): 365-371. DOI: 10.5768/JAO201637.0302001
    [8]WANG Min, ZHOU Lei, ZHOU Shu-dao, YE Song. Image SVD denoising based on PSNR and wavelet directional feature[J]. Journal of Applied Optics, 2013, 34(1): 85-89.
    [9]KUANG Hai-peng, WANG De-jiang, ZHANG Jing-guo, CHEN Zhi-chao, ZHANG Xue-fei, LIU Zhiming. Aerial image wavelet transformation denoising based on medium pre-filtering[J]. Journal of Applied Optics, 2010, 31(2): 221-224.
    [10]WANG Yu-tian, LI Yan-chun. Application of wavelet threshold denoising method in the fluorescence analysis of pesticides[J]. Journal of Applied Optics, 2006, 27(3): 192-194.

Catalog

    Article views (2227) PDF downloads (313) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return