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Study of joint CAMS/BRAMS observations & comparison with simulations

Study of joint CAMS/BRAMS observations & comparison with simulations. H. Lamy. Forward scatter radio observations. 2 advantages : Continuous monitoring Sensitive to smaller masses. Duration of the meteor echo depends roughly on the size of the object

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Study of joint CAMS/BRAMS observations & comparison with simulations

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  1. Study of joint CAMS/BRAMS observations &comparison with simulations H. Lamy

  2. Forwardscatter radio observations • 2 advantages: • Continuous monitoring • Sensitive to smaller masses • Duration of the meteorechodependsroughly on the size of the object • Most meteorechoes last a fraction of a second.

  3. The BRAMS network • 49.97 MHz • 150 W • pure sine wave • circularly polarized

  4. The BRAMS network University of Mons Maasmechelen Uccle Neufchâteau

  5. A typicalreceiving BRAMS station

  6. Example of BRAMS data  3 MB per file every 5 min 1 GB of data per day and per station WAV-format

  7. Spectrograms 200 Hz 5 minutes NFFT = 16384 – overlap = 90%  t  0,34 sec (real  2,97 sec) and f  0,3 Hz

  8. General idea • We are still struggling with the algorithms to retrieve meteoroid trajectories from BRAMS multi-stations observations. • Meanwhile we propose to use CAMS observations above Belgium which provide very accurate trajectories and speeds

  9. CAMS observations Credit : P. Roggemans Provide very accurate trajectories, speed and deceleration measurements Jenniskens et al (2016)

  10. CAMS observations • Night from 19 to 20 January : 245 trajectories • Trajectory 240 : • V_ = 66.33  0.15 km/s • a1 = 0.017  0.01 km/s • a2 = 0.398  0.08 s-1 • Lat, Long, H of begin and end points of CAMS trajectory • Begin time of observation of CAMS trajectory

  11. BRAMS observations : specularity condition

  12. Red : CAMS visual trajectory CAMS t_begin CAMS t_end Tx Rx1 Rx2 Rx3

  13. CAMS/BRAMS 1st comparison Night from 19 to 20/01/2017 : 245 trajectories Trajectory 240 Not all stations were working nominally !

  14. CAMS/BRAMS 1st comparison Zt =102.3 km Zt =93.1 km

  15. CAMS/BRAMS 1st comparison Zt = 117.4 km Zt = 120.5 km

  16. Comparison with meteor profiles

  17. Amplitude (a.u.) Time (sec) Blackman filter

  18. CAMS/BRAMS more accuratecomparison Check that the time corresponding to (e.g.) Half Maximum Power is close to the theoretical time due to specular reflection

  19. Determination of peak power Ppeak-under = Mc Kinley (1961)

  20. Gains of the Tx / Rxantennas   GR(,) Credit : A. Martinez Picar

  21. Calibration of peak power : the BRAMS calibrator

  22. Calibration of peak power « Calibrated » value by determining the amplitude of the calibrator signal Ppeak-under in Watts

  23. Limitations • Mc Kinley’s formula is strictly valid for underdense meteor echoes. Quid for overdense ones or even those with intermediate electron line densities? • Most antennas were tilted at that time, which means that their gain GR(,) is not very well constrained in the direction to the reflection point. • For the polarisation factor, we can tentatively take ½ (assuming we emit a circularly polarised wave, which is not exactly the case) • We have also to check the stability of the calibrator over time • Not all stations were working nominally at that time (problems with receiver, no calibrator everywhere, mismatch of antennas, etc…)

  24. Electron line densities We obtain the linear electron line density  in different points along the meteoroid path

  25. Comparisonwith simulations First, with a relatively simple model such as the one from Vondrak et al (2008). Matlab code available from VKI • V and  given by CAMS • massumedwithtypical values (unlessother information available) • Onlyunknownremains the mass

  26. Comparisonwith simulations q is the ionisation rate (in e-/m3) General idea : • Run the model for several « reasonable » values of the initial mass. Each model produces a profile of q as a function of the distance along the meteoroid path • Pick up the value of the mass that minimizes (in least square sense) the difference between simulated values and values obtained from BRAMS data • For that, establish link between q and 

  27. Perspectives • Correct the existing codes to analyze BRAMS/CAMS data and make them robust • Run the Matlab codes for the Vondrak model and pick up the best solution • Use more recent data from 4/5 October 2018 – 522 orbits • Present these results at EGU meeting – Vienna – 7-12 April 2019 • Publish the results • Explore other possibilites to decrease the aforementioned limitations

  28. Thank you

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