Improving the Accuracy of AIS Data Missing Value Imputation Using an Enhanced Interpolation Method

Qian Gao; Shaoyi Guo

doi:10.6919/ICJE.202504_11(4).0057

Authors

Qian Gao
Shaoyi Guo

DOI:

https://doi.org/10.6919/ICJE.202504_11(4).0057

Keywords:

Enhanced Hybrid Interpolation Method; Interpolation; AIS Data Preprocessing.

Abstract

During navigation, vessels continuously transmit Automatic Identification System (AIS) data, which contains a wealth of information. However, raw AIS data is often disorganized and may contain anomalies or missing values, making it difficult to directly track navigation trajectories. To make these data usable and ensure their integrity while reducing subsequent trajectory prediction errors, it is essential to preprocess the raw AIS data. This involves extracting and constructing a dataset of vessel navigation trajectories using the latitude and longitude of vessels entering and leaving ports, as well as the latitude, longitude, speed, and navigation status of AIS trajectory points. Subsequently, the extracted navigation trajectory data is preprocessed to remove anomalies. Finally, an enhanced hybrid interpolation method is employed to impute missing trajectory data, thereby improving the accuracy of interpolation.

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References

[1] Zhen R, Shao Z P, Pan J C. Research progress and prospects on ship behavior feature mining and prediction based on AIS data[J]. Journal of Earth Information Science, 2021, 23(12): 2111-2127.

[2] Zhou C, Liu W D, Wan G H, et al. Application of spline interpolation in AIS data repair[J]. China Water Transport. Channel Technology, 2018, (04): 76-79. DOI: 10.19412/j.cnki.42-1395/u.2018.04.016.

[3] Liu L Q, Wu C Z, Chu D F, et al. Research on ship trajectory repair based on Vondrak filtering and cubic spline interpolation[J]. Traffic Information and Safety, 2015, 33(04): 100-105.

[4] Guo S, Mou J, Chen L, et al. Improved Kinematic Interpolation for AIS Trajectory Reconstruction[J]. Ocean Engineering, 2021, 234(8).

[5] Zhou Y, Mu F, Hu J. Adaptive state updating particle filter tracking algorithm based on cubic spline interpolation[C]//2021 International Conference on Electronic Information Engineering and Computer Science (EIECS). IEEE, 2021: 484-488.

[6] Noor N M, Al Bakri Abdullah M M, Yahaya A S, et al. Comparison of linear interpolation method and mean method to replace the missing values in environmental data set[C]//Materials Science Forum. Trans Tech Publications Ltd, 2015, 803: 278-281.