WANG Zhigang, BIAN Shaofeng. Passive Location of Underwater Target Based on Local Gravity Field Model[J]. Geomatics and Information Science of Wuhan University, 2008, 33(9): 918-921.
Citation: WANG Zhigang, BIAN Shaofeng. Passive Location of Underwater Target Based on Local Gravity Field Model[J]. Geomatics and Information Science of Wuhan University, 2008, 33(9): 918-921.

Passive Location of Underwater Target Based on Local Gravity Field Model

Funds: 国家杰出青年科学基金资助项目(40125013)
More Information
  • Received Date: July 28, 2008
  • Revised Date: July 28, 2008
  • Published Date: September 04, 2008
  • A new pattern for passive location which based on local gravity field model is presented.A fast Fourier series based local gravity field model is firstly introduced,then by which the measured gravity is expressed as continual analytical equation.Finally the classical extended Kalman filter is introduced to estimate the target position with measured gravity as measurement containing the information of target positon.Simulation is done on 0.2′×0.2′ gravity anomaly database,the result shows that the mean error of analytic equation of local gravity anomalies is less than 0.133 1 mGal,and the mean location errors in longitude and latitude are less than 0.777 0 nmile and 1.244 4 nmile respectively.
  • Related Articles

    [1]LONG Yujie, LI Weile, HUANG Runqiu, XU Qiang, YU Bin, LIU Gang. Automatic Extraction and Evolution Trend Analysis of Landslides in Mianyuan River Basin in the 10 Years After Wenchuan Earthquake[J]. Geomatics and Information Science of Wuhan University, 2020, 45(11): 1792-1800. DOI: 10.13203/j.whugis20200180
    [2]HE Chu, LIU Ming, XU Lianyu, LIU Longzhu. A Hierarchical Classification Method Based on Feature Selection and Adaptive Decision Tree for SAR Image[J]. Geomatics and Information Science of Wuhan University, 2012, 37(1): 46-49.
    [3]XIONG Biao, JIANG Wanshou, LI Lelin. Gauss Mixture Model Based Semi-Supervised Classification for Remote Sensing Image[J]. Geomatics and Information Science of Wuhan University, 2011, 36(1): 108-112.
    [4]TAO Jianbin, SHU Ning, GONG Yan, SHEN Zhaoqing. An Instructed Unsupervised Classification Method for Remote Sensing Image Based on Gaussian Mixture Model[J]. Geomatics and Information Science of Wuhan University, 2010, 35(6): 727-732.
    [5]SHEN Zhaoqing, SHU Ning, TAO Jianbin. An Algorithm of Weighted “1 V m” SVM Multi-classification for Hyperspectral Remote Sensing Image with NPA[J]. Geomatics and Information Science of Wuhan University, 2009, 34(12): 1444-1447.
    [6]ZOU Tongyuan, YANG Wen, DAI Dengxin, SUN Hong. An Unsupervised Classification Method of POLSAR Image[J]. Geomatics and Information Science of Wuhan University, 2009, 34(8): 910-913.
    [7]YIN Shuling, SHU Ning, LIU Xinhua. Classification of Remote Sensing Image Based on Adaptive GA and Improved BP Algorithm[J]. Geomatics and Information Science of Wuhan University, 2007, 32(3): 201-204.
    [8]CHEN Ziyi, KANG Lishan. Multi-Parent Crossover Evolutionary Algorithm for Constrained Optimization[J]. Geomatics and Information Science of Wuhan University, 2006, 31(5): 440-443.
    [9]CHENMi, YIYaohua, LIDeren, QINQianqing. Application of Projection Pursuit Based on Dynamical Evolutionary Algorithm to Anomaly Target Detection in Hyperspectral Images[J]. Geomatics and Information Science of Wuhan University, 2006, 31(1): 55-58.
    [10]Zheng Zhaobao, Zheng Hong. The Image Texture Classification Based on Genetic Algorithms[J]. Geomatics and Information Science of Wuhan University, 1998, 23(4): 337-339.

Catalog

    Article views (874) PDF downloads (449) Cited by()
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return