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Volume 40 Issue 7
Jul.  2018
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LIU Yong, YAO Libo, WU Yuzhou, XIU Jianjuan, ZHOU Zhimin. Target Point Tracks Association and Error Correction with Optical Satellite in Geostationary Orbit and Automatic Identification System[J]. Journal of Electronics & Information Technology, 2018, 40(7): 1546-1552. doi: 10.11999/JEIT170896
Citation: LIU Yong, YAO Libo, WU Yuzhou, XIU Jianjuan, ZHOU Zhimin. Target Point Tracks Association and Error Correction with Optical Satellite in Geostationary Orbit and Automatic Identification System[J]. Journal of Electronics & Information Technology, 2018, 40(7): 1546-1552. doi: 10.11999/JEIT170896

Target Point Tracks Association and Error Correction with Optical Satellite in Geostationary Orbit and Automatic Identification System

doi: 10.11999/JEIT170896
Funds:

The National Natural Science Foundation of China (91538201)

  • Received Date: 2017-09-22
  • Rev Recd Date: 2018-03-07
  • Publish Date: 2018-07-19
  • When ship target is monitored by the geostationary optical satellite, the positioning error is large due to the long distance between the target and the satellite, which affects the accuracy of the follow-up target tracking. As the monitoring area is mainly the ocean, it may not be possible to find the Ground Control Point (GCP) for coordinate correction. In order to improve the positioning accuracy of the geostationary optical satellite for ship without GCP, and to realize the fusion of multi-source data, a novel target point association and error correction with optical satellite in geostationary orbit and ship Automatic Identification System (AIS) is proposed. By means of the Rational Polynomial Coefficient (RPC) model, AIS coordinates are transformed into image coordinates. The Iterative Closest Point (ICP) and Global Nearest Neighbor (GNN) algorithm are combined and used for data association. Then, the error is corrected using the point pair of association. Experimental results using GF-4 images and AIS data verify the feasibility of the proposed method and show that the association algorithm has a high correlation rate, and the average positioning accuracy after error correction is improved greatly compared with the positioning accuracy before correction.
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