Data cleaning method of ADS-B historical flight trajectories

WANG Bing

doi:10.19818/j.cnki.1671-1637.2020.04.018

Volume 20 Issue 4

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Article Navigation > Journal of Traffic and Transportation Engineering > 2020 > 20(4): 217-226

WANG Bing. Data cleaning method of ADS-B historical flight trajectories[J]. Journal of Traffic and Transportation Engineering, 2020, 20(4): 217-226. doi: 10.19818/j.cnki.1671-1637.2020.04.018

Citation:

WANG Bing. Data cleaning method of ADS-B historical flight trajectories[J]. Journal of Traffic and Transportation Engineering, 2020, 20(4): 217-226. doi: 10.19818/j.cnki.1671-1637.2020.04.018

WANG Bing. Data cleaning method of ADS-B historical flight trajectories[J]. Journal of Traffic and Transportation Engineering, 2020, 20(4): 217-226. doi: 10.19818/j.cnki.1671-1637.2020.04.018

Citation:

WANG Bing. Data cleaning method of ADS-B historical flight trajectories[J]. Journal of Traffic and Transportation Engineering, 2020, 20(4): 217-226. doi: 10.19818/j.cnki.1671-1637.2020.04.018

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Data cleaning method of ADS-B historical flight trajectories

doi: 10.19818/j.cnki.1671-1637.2020.04.018

WANG Bing¹

1.
College of Civil Aviation/College of Flight, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, Jiangsu, China
2.
National Key Laboratory of Air Traffic Flow Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, Jiangsu, China

Funds:

National Natural Science Foundation of China 61903187

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Author Bio:
WANG Bing(1979-), male, lecturer, PhD, evanwb@163.com
Received Date: 2020-02-02
Publish Date: 2020-04-25

Abstract

Abstract

To effectively solve the various field data anomalies in the automatic dependent surveillance-broadcast(ADS-B) historical flight trajectories affected by the ground station distribution breadth, terrain blocking, electromagnetic interference and so on, an ADS-B data cleaning method was established, and implemented by four steps, such as determining the cleaning object, deleting the duplication of field, cleaning the abnormal point and correcting the time stamp. According to the existing sample ADS-B historical data, the track model was established and the validity was analyzed. The fields such as the time stamp, longitude, latitude, pressure altitude and ground speed were defined as the characteristic fields and cleaning objects. The time stamp, longitude and latitude of ADS-B track point sequence were deduplicated to delete the adjacent track points with repeated data. The outliers of characteristic fields were located through the method based on the density-based spatial clustering of applications with noise(DBSCAN) to improve the cleaning efficiency, detect and correct the abnormality. To make the change of track point state conform to the particle kinematic law, the time stamp was corrected by the field data of longitude, latitude, pressure altitude and ground speed of ADS-B track points, and the extended modified time stamp field was saved. Research result shows that 97.58% of the abnormal track points in the 516 sample flights are effectively identified and cleaned. The cleaned track point state changes more smoothly. The total flight duration before and after correction varies between 10-600 s. The correction effect of time stamp mainly depends on the accuracy of ground speed. The corrected time stamp should be selectively used according to the data characteristics of sample track in practical engineering applications. The established cleaning method of ADS-B data can provide a preliminary data processing platform for the trajectory analysis, evaluation and computing in civil aviation engineering projects.
- air traffic,
- ADS-B flight trajectory,
- data cleaning,
- DBSCAN method,
- local traversal,
- time stamp correction

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References(30)

References

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Data cleaning method of ADS-B historical flight trajectories

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