Effective Association of SAR and AIS Data Using Non-Rigid Point Pattern Matching

35th International Symposium on Remote Sensing of Environment

地球科学;生态环境科学

Zhao, Z.^1 ; Ji, K.F.^1 ; Xing, X.W.^1 ; Zou, H.X.^1

School of Electronic Science and Engineering, National University of Defence Technology, Changsha, Hunan 410073, China^1

关键词: Automatic identification system;    Coherent point drifts;    Joint probabilistic data association;    Multiple hypothesis testing;    Navigational information;    Non-rigid;    Non-rigid point pattern-matching;    Point pattern matching;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/17/1/012258/pdf
DOI  :  10.1088/1755-1315/17/1/012258

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Ship surveillance using multiple remote sensing sensors becomes more and more vital presently. Among the various sensors, space-borne Synthetic Aperture Radar (SAR) is optimal for its high resolution over wide swaths and all-weather working capabilities. Meanwhile, Automatic Identification System (AIS) is efficient to provide ship navigational information. Limited to the progress of ship surveillance using SAR image only, the integration of them significantly benefits more. Data association is the fundamental issue. Many algorithms have been developed including the Nearest-Neighbour (NN) algorithm, the Joint Probabilistic Data Association (JPDA) method, and the Multiple Hypothesis Testing (MHT) approach. Ship positions derived from SAR image can be associated with the ones provided by AIS. State-of-the-art method (NN algorithm) is proved to be feasible. But it faces more challenges under adverse circumstances, such as high-density-shipping condition. We investigate the non-rigid Point Pattern Matching (PPM) method to solve this problem. To the best of our knowledge, this paper is the first to introduce non-rigid PPM to the data association of SAR and AIS. On the basis of introduction to the data association, Coherent Point Drift (CPD) algorithm is investigated. Experiments are carried out and the results illustrate that the CPD algorithm achieves higher accuracy and outperforms state-of-the-art method, especially under high-density-shipping condition.