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Analysis of bird situation around airports using avian radar

Published online by Cambridge University Press:  08 July 2021

W.S. Chen
Affiliation:
[email protected] Airport Research Institute China Academy of Civil Aviation Science and Technology100028BeijingChina
Y.F. Huang
Affiliation:
[email protected] Airport Research Institute China Academy of Civil Aviation Science and Technology100028BeijingChina
X.F. Lu
Affiliation:
[email protected] Airport Research Institute China Academy of Civil Aviation Science and Technology100028BeijingChina
J. Zhang
Affiliation:
[email protected] Airport Research Institute China Academy of Civil Aviation Science and Technology100028BeijingChina

Abstract

To improve the ability of avian radar to process bird information, a statistical analysis method for the bird situation around airport is proposed based on avian radar data. By accumulating a large amount of avian radar data, hotspots of the activity area of bird targets can be determined and taken as a reference point to realise lifecycle management of each bird target from initiation to continuation and finally death. In the process of target tracking, combined with the particle filter method, the probability of several possible events is estimated, leading to completion of the data association and real-time statistics for the number of targets. The simulation results reveal that this method is superior to the traditional logic method regarding the timeliness of multi-target initiation. With the application of the proposed method to avian radar data, the bird population and its basic activity rules can be discovered by fixing the bird habitats around the airport.

Type
Research Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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References

REFERENCES

AC No: 150/5200-32B FAA Advisory Circular on Reporting Wildlife Aircraft Strikes, 2013.Google Scholar
Ning, H.S., Liu, W.M., Li, J. and Zhao, X.R. Research on radar avian detection for aviation, Acta Electron. Sin., 2006, 34, (12), pp. 22322237.Google Scholar
Nohara, T.J. Could avian radar have prevented US Airways flight 1549’s bird strike? Proceedings of the Bird Strike North America. Vancouver, British Columbia, Canada, 2010.Google Scholar
Federal Aviation Administration. Advisory Circular (No. 150/5200-38), 2018.Google Scholar
International Civil Aviation Organization. Wildlife Control and Reduction, Airport Services Manual (Doc 9137, AN/898, Part 3), 2012.Google Scholar
Airport Bureau of CAAC. Guide for investigation of bird situation and ecological environment of Civil Airports (AC-140-CA-2009-2), Aug. 18, 2009.Google Scholar
Beason, R.C., Nohara, T.J. and Weber, P. Beware the Boojum: caveats and strengths of avian radar, Hum. Wildl. Interact., 2013, 7(1), 1646.Google Scholar
Gerringer, M.B., Lima, S.L. and DeVault, T.L. Evaluation of an avian radar system in a mid-western landscape, Wildl. Soc. Bull., 2016, 40, (1), 150159.CrossRefGoogle Scholar
Nilsson, C., Dokter, A.M., Schmid, B., Scacco, M., Verlinden, L., Bckman, J., Haase, G., Dell'Omo, G., Chapman, J.W. and Leijnse, H. Field validation of radar systems for monitoring bird migration, J. Appl. Ecol., 2018, 55, (6), 25522564.CrossRefGoogle Scholar
Chen, W.S. and Li, J. Review on development and applications of avian radar technology, Mod. Radar, 2017, 39, (2), 717.Google Scholar
Chen, W.S., Zhang, J. and Lu, X.F. Airport bird situation analysis based on avian radar data, China Civil Aviation, 2020, 313, 4345.Google Scholar
He, Y., Xiu, J.J., Zhang, J.W. and Guan, X. Radar data processing with applications[M], Beijing: Publishing House of Electronics Industry, 2009.Google Scholar
Granstrom, K. and Baum, M. Extended object tracking: introduction, overview and applications, J. Adv. Inform. Fusion, 2017, 12, (2), 139174.Google Scholar
Hu, Z.J. and Leung, H. Statistical performance analysis of track initiation techniques, IEEE Trans. Aerosp. Electron. Syst., 1997, 45, (2), 445456.Google Scholar
Wang, G.H., Su, F. and He, Y. Hough transform and logic based track initiator in three dimensional space, Acta Simul. Syst. Sin., 2004, 16, (8), 21982200.Google Scholar
Carlson, B.D., Evans, E.D. and Wilson, S.L. Search radar detection and track with the Hough transform, IEEE Trans. Aerosp. Electron. Syst., 1994, 30, (1), 102108.CrossRefGoogle Scholar
Li, L., Wang, G., Zhang, X.Y. and Yu, H.B. The track initiation algorithm based on Hough transform and space accumulation, Proceeding of the IEEE International Conference on Signal Processing, 2017, pp. 1466–1470.Google Scholar
Shi, J.T., Sun, J., Yang, Y.H. and Wang, N. A study and application of track initiation of sea surface targets based on machine learning support vector machine, Mod. Radar, 2019, 41, (11), 2029.Google Scholar
Yang, C.F., Liu, S., Li, H.B. and Zhang, Y. A new track initiation algorithm based on random forest, Inf. Res., 2018, 44, (6), 1620.Google Scholar
Jounny, I. and Garbar, F.D. Classification of radar target using synthetic neural network, IEEE Trans. Aerosp. Electron. Syst., 1993, 29, (2), 336343.10.1109/7.210072CrossRefGoogle Scholar
Sun, X.J. and Yang, G.M. Multi-sensor optimal weighted fusion incremental Kalman smoother, J. Syst. Eng. Electron., 2018, 29, (2), 262268.CrossRefGoogle Scholar