Current Optics and Photonics

Optical Society of Korea (한국광학회)
권호 표지
DOI QR코드

DOI QR Code

A Novel Ramp Method Based on Improved Smoothing Algorithm and Second Recognition for Windshear Detection Using LIDAR

  • Li, Meng (Civil Aviation Meteorological Institute, Key Laboratory of Operation Programming & Safety Technology of Air Traffic Management, Civil Aviation University of China) ;
  • Xu, Jiuzhi (Civil Aviation Meteorological Institute, Key Laboratory of Operation Programming & Safety Technology of Air Traffic Management, Civil Aviation University of China) ;
  • Xiong, Xing-long (College of Precision Instrument and Optoelectronics Engineering, Key Lab of Optoelectronic Information Technology (Ministry of Education), Tianjin University) ;
  • Ma, Yuzhao (College of Precision Instrument and Optoelectronics Engineering, Key Lab of Optoelectronic Information Technology (Ministry of Education), Tianjin University) ;
  • Zhao, Yifei (Civil Aviation Meteorological Institute, Key Laboratory of Operation Programming & Safety Technology of Air Traffic Management, Civil Aviation University of China)
  • Received : 2017.10.30
  • Accepted : 2017.12.14
  • Published : 2018.02.25
Download PDF
⟨ Previous Next ⟩

Abstract

As a sophisticated detection technology, LIDAR has been widely employed to probe low-altitude windshear. Due to the drawbacks of the traditional ramp algorithm, the alarm accuracy of the LIDAR has not been satisfactory. Aiming at settling this matter, a novel method is proposed on the basis of improved signal smoothing and second windshear detection, which essentially acts as a combination of ramp algorithm and segmentation approach, involving the human factor as well as signal fluctuations. Experiments on the real and artificial signals verify our approach.

Keywords

KGHHD@_2018_v2n1_7_f0001.png 이미지

FIG. 1. Schematic diagram of glide path scan of LIDAR.

KGHHD@_2018_v2n1_7_f0002.png 이미지

FIG. 2. The headwind profiles with common windshear (b) and special windshear that contains a flat area (a).

KGHHD@_2018_v2n1_7_f0003.png 이미지

FIG. 3. The flowchart of the proposed approach for windshear detection.

KGHHD@_2018_v2n1_7_f0004.png 이미지

FIG. 4. Schematic diagram of simplification method: the first iteration (a), the second iteration (b) and final simplified signal (c). The curve and straight lines express the original and simplified signals, respectively.

KGHHD@_2018_v2n1_7_f0005.png 이미지

FIG. 5. Flat area detection with linear simplification method and a two-dimensional threshold.

KGHHD@_2018_v2n1_7_f0006.png 이미지

FIG. 6. Three artificial test signals: the common windshear (a), the windshear divided by a flat area (b) and one disturbed by a peak (c).

KGHHD@_2018_v2n1_7_f0007.png 이미지

FIG. 7. Two real headwind profiles are divided by flat areas on.8:25 UTC 12 March 2007 (a) and 8:28 UTC 12 March 2007 (b). The ramp algorithm is used to determine the windshear ranges, shown as dashed boxes. Flat areas are marked by vals. Additionally, we display the simplified curve with dashed lines. (a) Pilot report: windshear 10 kt. (b) Pilot report: non-windshear.

KGHHD@_2018_v2n1_7_f0008.png 이미지

FIG. 8. The range errors of headwind profiles caused by smoothing (a) and flat area (c), and the false alarms of ones caused by smoothing (b) and flat area (d). The solid and dashed line boxes indicate the ramp algorithm and our method respectively.

KGHHD@_2018_v2n1_7_f0009.png 이미지

FIG. 9. The performance of low-level windshear alerting on corridors 07LA (a) and 25RA (b) at HKIA using two methods along glide-paths over January to September, 2014-2016.

TABLE 1. Three possible cases after signal processing with two kinds of “smoothing method”

KGHHD@_2018_v2n1_7_t0001.png 이미지

TABLE 2. The detection results using two methods in different SNR

KGHHD@_2018_v2n1_7_t0002.png 이미지

References

  1. C. Moscardini, F. Berizzi, M. Martorella, and A. Capria, "Signal spectral modelling for airborne radar in the presence of windshear phenomena," IET Radar Sonar Navigation 5(7), 796-805 (2011). https://doi.org/10.1049/iet-rsn.2010.0234
  2. K. K. Hon and P. W. Chan, "Application of LIDAR -derived eddy dissipation rate profiles in low -level wind shear and turbulence alerts at Hongkong international airport," Meteorol. Appl. 21(1), 74-85 (2014). https://doi.org/10.1002/met.1430
  3. M. J. Ma, C. Lin, S. R. Zhao, B. K. Zhang, H. X. Shen, S. G. Wang, "Characteristics and a numerical study of low-level windshear over Beijing Capital International Airport," J. Lanchow Univ., Nat. Sci. 7(49), 354-360 (2013).
  4. R. B. Wu, Z .C. Meng, Y. Fan, Z. G. Sun, X. G. Lu, and J. H. Huang, "Windshear signal simulation of the airborne weather radar," Modern Radar 8(34), 74-78 (2012).
  5. J. Gao and Y. Zhao, "Simulation research on windshear prediction of airborne weather radar," Virtual Reality and Visualization (ICVRV), 2014 International Conference on. 8, 435-438 (2014).
  6. M. E. Weber and M. L. Stone, "Low altitude windshear detection using airport surveillance radars," IEEE Aerosp. Electron. Syst. Mag. 10(6), 3-9 (1995). https://doi.org/10.1109/62.387970
  7. N. Chen, Z. Qian, and X. F. Meng, "Wind power forecasts using gaussian processes and numerical weather prediction," IEEE Trans. Power Syst. 29(2), 656-665 (2014). https://doi.org/10.1109/TPWRS.2013.2282366
  8. S. C. Medeiros, S. C. Hagen, and J. F. Weishampel, "A random forest model based on LIDAR and field measurements for parameterizing surface roughness in coastal modeling," IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. 8(4), 1582-1590 (2015). https://doi.org/10.1109/JSTARS.2015.2419817
  9. M. Wang and Y. H. Tseng, "Automatic segmentation of LIDAR data into coplanar point clusters using an octree-based split-and-merge algorithm," Photogramm. Eng. Remote Sens. 76, 407-420 (2010). https://doi.org/10.14358/PERS.76.4.407
  10. K. K. Hon and P. W. Chan, "Application of LIDAR-derived eddy dissipation rate profiles in low-level windshear and turbulence alerts at Hong Kong international airport," Meteorol. Appl. 21, 74-85 (2014). https://doi.org/10.1002/met.1430
  11. C. M. Shun and P. W. Chan, "Applications of an infrared doppler LIDAR in detection of windshear," J. Atmos. Oceanic Technol. 5(25), 637-655 (2008).
  12. H. Uyeda and D. S. Zrnic, "Automatic detection of gust fronts," J. Atmos. Oceanic Technol. 3(1), 36-50 (1986). https://doi.org/10.1175/1520-0426(1986)003<0036:ADOGF>2.0.CO;2
  13. L. G. Hermes, A. Witt, S. D. Smith, D. Klingle-Wilson, D. Morris, G. J. Stumpf, and M. D. Eilts, "The gust-front detection and wind-shift algorithms for the terminal doppler weather radar system," J. Atmos. Oceanic Technol. 10(5), 693-709 (1993). https://doi.org/10.1175/1520-0426(1993)010<0693:TGFDAW>2.0.CO;2
  14. Y. F. Lee and P. W. Chan, "LIDAR-based F-factor for wind shear alerting: different smoothing algorithms and application to departing flights," Meteorol. Appl. 21(1), 86-93 (2014). https://doi.org/10.1002/met.1434
  15. M. Bilgili, B. Sahin, and A. Yasar, "Application of artificial neural networks for the wind speed prediction of target station using reference stations data," Renewable Energy 32(14), 2350-2360 (2007). https://doi.org/10.1016/j.renene.2006.12.001
  16. A. More and M. C. Deo, "Forecasting wind with neural network," Mar. Struct. 16(1), 35-49 (2003). https://doi.org/10.1016/S0951-8339(02)00053-9
  17. N. K. Liu, K. M. Kwong, and P. W. Chan, "Chaotic Oscillatory-based neural network for windshear and turbulence forecast with lidar data," IEEE Trans. Syst., Man, Cybern., Part C 10(6), 1412-1423 (2012).
  18. K. Nakamura, K. Muramoto, and T. Ohigashi, Visualization of water vapor distribution in the lower atmosphere using two LIDARs (ICROS-SICE International Joint Conference 2009), pp. 5445-5450.
  19. N. Manago and G. Bagtasa, Multi-wavelength LIDAR system for the characterization of tropospheric aerosols and clouds (2012 IEEE International Geoscience and Remote Sensing Symposium), pp. 2505-2508.
  20. P. W. Chan, C. M. Shun, and K. C. Wu, Operational LIDAR-based system for automatic windshear alerting at the Hong Kong international airport (12th Conference on Aviation, Range, and Aerospace Meteorology, 2006).
  21. J. Lihui, Y. Yan, X. Xinglong, C. Bowei, C. Xing, and Z. Dian, "Doppler LIDAR alerting algorithm of low-level windshear based on ramps detection," Infrared Laser Eng. 45(1), 106001-0106001 (2016).
  22. A. A. Woodfield and J. F. Woods. Worldwide experience of windshear during 1981-1982 (AGARD Flight Mechanics Panel Conference on 'Flight Mechanics and System Design Lessons from Operational Experience', 1983).