1 / 20

Lightning detection and localization using extended Kalman filter

National Engeneering School of Tunis. Lightning detection and localization using extended Kalman filter. Ines Ben Saïd U2S(ENIT) SYS’COM Master 2008-2009. U2S. References.

lelia
Télécharger la présentation

Lightning detection and localization using extended Kalman filter

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. National Engeneering School of Tunis Lightning detection and localization using extended Kalman filter Ines Ben Saïd U2S(ENIT) SYS’COM Master 2008-2009 U2S

  2. References 1 - T. G. Wood, Geo-location of individual lightning discharges using impul- sivevlf electromagnetic waveforms, Phd thesis, The department of electrical engineering and the committee on graduate studies of stanford university, De- cember 2004. 2 - S. A. Cummer, Lightning and ionospheric remote sensing using vlf/elf radio atmospherics, Phd thesis, The department of electrical engineering and the committee on graduate studies of stanford university, August 1997. 3 - R. E. Kalman, A new approach to linear filtering and prediction problems, Transaction of the ASME Journal of Basic Engineering, (pp. 35{45), March 1960. 2

  3. Lightning Detection Earth+ Ionosphere = waveguide [ELF-VLF] = [300Hz-30KHz] Receivers Transmitters radio atmospherics (‘sferic’) = Waves that propagates in the ELF/VLF band with low attenuation (~3dB/1000Km) Lightning detection via VLF data analyses 3

  4. VLF receiver at LSAMA Hardware Software 4

  5. VLF receiver schema A/D Converter Two data types: - narrow band - broad band 5

  6. Broad band signals transmitters sferic 6

  7. Sferic caracteristics (Cummer 2004 ) • Much of the sferic energy lies in [5KHz-15KHz] band (Cummer 2004 ) • Duration ~4ms: - ~ 1ms VLF impulse - ~ 3ms ELF slow tail 7

  8. Sferics detection method Proposed procedure N = 60000 samples Te = 100KHz • Identification • Two successif instants must be separated with an delay >= 4ms (sferic duration) • Determinate the simultaneous instants for the N/S and E/W signals. 8

  9. Lightning localizationIMPACT Tow receivers are sufficient Precision depend on optimization method 9

  10. Lightning localization Arrival azimuth calculation 10

  11. Triangulation 11

  12. Results and limites IMPACT method tested by simulation Source [45°N 60°E] 1st receiver : Vieques 2nd receiver : Palmer 12

  13. Proposed method: Extended Kalman filter Interest : non linear optimization used in GPS localization Observation State State representation 13

  14. Algorithm Initialisation Prediction Correction 14

  15. Simulation results Source P1 [45°N 60°E] 1st receiver A: Vieques 2nd receiver B: Palmer Estimated position 15

  16. Simulations results Real Source [45°N 60°E] 1st receiver A: Vieques 2nd receiver B: Palmer Azimuth error 1°; Time difference Error 0.1ms Real source Estimated position 16

  17. Real data 17

  18. Real data localization Extended kalman filter Researsh zone Alger Alger Iso time difference Iso time difference • Source localized in the triangle using the two methods • A difference of ~200Km between the two methods 18

  19. Conclusion and perspective Automatic method for sferic detection Localization using extended Kalman filter Introduction of signal dynamic in physics problems Test of other optimization methods 19

  20. THANK YOU

More Related