SB10
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Orals: Fri, 23 Sep | Room Albéniz+Machuca
When meteoroids hit Earth’s atmosphere molecules, they leave a trail of plasma behind. This region, composed of free electrons and positively charged ions, is capable of reflecting radio signals. The analysis of such signals along the meteoroid path can be used for various scientific purposes: quantification of the electron line density, analysis of the thermosphere properties, characterization of the meteor ablation process, etc. To achieve these objectives, the meteoroid trajectory needs first to be determined.
The reflection on the plasma trails is usually assumed to be specular, which means that the radio wave is reflected only at a given point along the meteoroid trajectory. For forward scatter systems, the position of this specular point depends on the trajectory on the one hand, and on the position of both the emitter and the receiver on the other hand. Using non-collocated receivers, one obtains several specular points along the trajectory. The receivers will thus detect the reflected signal at different time instants on a given trajectory.
In this work, we propose a method that aims at reconstructing meteoroid trajectories using only the time differences of the meteor echoes measured at the receivers of a forward scatter radio system, such as the BRAMS (Belgian RAdio Meteor Stations) network. The latter uses the forward scatter of radio waves on ionized meteor trails to study meteoroids falling in the Earth’s atmosphere. It is made of a dedicated transmitter and 42 receiving stations located in and nearby Belgium. Given that all the BRAMS receivers are synchronized using GPS clocks, we can compute the time differences of the meteor echoes and use them to find the meteoroid trajectory.
Assuming a constant speed motion, the position (three degrees of freedom) and the three velocity components have to be determined. This inverse problem is non-linear and requires the definition of a target objective to minimize. Two different formulations are compared: the first one is based on the minimization of the bistatic range while the second one uses a forward model, which defines the trajectory as being tangential to a family of ellipsoids whose loci are the emitter and each receiver. A Monte-Carlo analysis is performed to highlight the sensitivity of the output trajectory parameters to the input time differences.
The BRAMS network also includes an interferometer in Humain (south of Belgium). Unlike the other receiving stations, it uses 5 antennas in the so-called Jones configuration (Jones et al., 1998; Lamy et al., 2018) and allows to determine the direction of arrival of the meteor echo to within approximately 1°. In that case, the problem becomes much easier to solve because the interferometer gives information about the direction of a reflection point. The benefits brought by such a system regarding the accuracy of the trajectory reconstruction are highlighted.
The post-processing steps allowing to extract meteor echoes from the raw radio signals are described. An approach to properly filter out the direct beacon signal is introduced. Indeed, each receiver detects a more or less strong direct signal coming from the transmitter. This signal does not contain any information about the meteor path since it simply propagates through the atmosphere and is not reflected on the meteor trail. Knowing that the BRAMS transmitter emits a continuous cosine wave, the amplitude, the frequency and the phase are fitted in the frequency domain. The beacon signal is finally reconstructed in the time domain and subtracted. This process in illustrated in the following figure, which shows an example of spectrograms (i.e. time-frequency maps where the power is color-coded) before and after the beacon signal subtraction. The proper removal of the horizontal line at around 1005 Hz (corresponding to the direct signal) is apparent in the bottom spectrogram.
Afterwards, a bandpass filter is necessary to fully exploit the echoes of the detected meteors. Indeed, the raw signal at the time of the meteor echo is noisy and can have interfering signals caused by the reflections on aircrafts. If the latter are at slightly different frequencies than the meteor echo, they produce interference beats. A windowed-sinc filter Blackman filter of high order is therefore used to remove the signal components at frequencies where the meteor echo does not appear. The time corresponding to half-peak power in the rising edge of the echo (which marks the passage of the meteoroid at the specular reflection point) is finally retrieved and the time differences are computed.
To analyze the accuracy of the trajectory reconstructions, data from the optical CAMS-BeNeLux network are used. Promising results showing the reconstructed position, velocity and inclination of several meteoroid trajectories with and without the interferometer are discussed. In the following figure, an example of CAMS trajectory reconstruction obtained with our post-processing is shown. The blue line corresponds to the trajectory determined with the CAMS network, while the purple line is obtained through our analysis of the radio signals obtained at the BRAMS receivers. The reconstructed trajectory using the time differences only (method 1) is shown on the left. The trajectory obtained thanks to the combination of time differences and interferometric data (method 2) is given on the right.
How to cite: Balis, J., Lamy, H., Anciaux, M., and Jehin, E.: Reconstructing meteoroid trajectories using forward scatter radio observations and the interferometer from the BRAMS network, Europlanet Science Congress 2022, Granada, Spain, 18–23 Sep 2022, EPSC2022-227, https://doi.org/10.5194/epsc2022-227, 2022.
Posters: Thu, 22 Sep, 18:45–20:15 | Poster area Level 2
Abstract
In this paper we present the results obtained from the spectral analysis using the wavelet technique of a time series of brightest fireballs to look for periodicities associated with other bodies of our Solar System. The spectra show four periodicities at 106.2 days, 12.7 days, 2.5 days, 10.3 years and 4.6 years. In particular the periodicities around 12.7 and 2.5 days could be related to the Carrington rotation period.
Introduction
One of the main problems of Planetary Sciences is to understand the dynamical behavior of asteroids, meteors and meteoroids inhabiting near our planet, mainly those that fall on terrestrial surface. These bodies feel the planetary and solar gravitational influence when they travel across the interplanetary medium or mainly when they are in the terrestrial neighborhood of one of those bodies. The detection of meteoroids falling on Earth using several instruments has been important because it has permitted to obtain very useful data. The analysis of these data can help to identify the physical interactions that occur between these bodies and the rest of the bodies in the solar system. Additionally in recent decades, multiple modeling and numerical simulation works have been carried out to fully understand the origin of such interactions.
The spectral method
A time series of brightest fireballs from January, 1998 to December, 2020 was spectrally studied using the wavelet technique to look for periodicities related with Solar System bodies relationships. The data were taken from the Near Earth Object Program (https://cneos.jpl.nasa.gov/fireballs). Because of this time series has gaps, the wavelet transform was used to do the spectral analysis. The method was applied using the Morlet function (eq. 1) [1] to analyze the power spectral density (PSD) of brightest fireball meteors [1], [2], [3].
(1)
Where ω0 and η are both non-dimensional frequency and time parameter respectively
Results and discussion
Five periodicities were identified from the wavelet spectral analysis (figure 1). They are located at 2.5 days, 12.7 days, 106.2 days, 4.6 years and 10.3 years. The figure 1 shows the power spectral density spectra (PSD) where these periodicities can be seen on the right side of the plot. They are inside the cone of influence (COI) and were obtained with a confidence level of 85%. The uncertainties of every peak position were obtained from the peak full width at half maximum.
Figure 1: PSD of a time series of brightest fireballs from January, 1998 to December, 2020. On the right side of the plot, five peaks at 2.5, 12.7 and 106.2 days and at 4.6 and 10.3 years are shown.
In particular the periodicity around 12.7 days could be the first harmonic of the Carrington rotation period (27 days), [4] indicating that the solar gravitational force could be modulating the meteoroids entrance on the Terrestrial atmosphere. Carrington rotation has been detected in several time series as is the case of solar spots, storm sudden commencements, cosmic rays, among others. The periodicity around 2.5 days, it could be a small harmonic of the solar rotation period.
The mechanism behind the relationship between the variable solar radiation (due to its rotation and the solar cycle) and the fall of small asteroids to Earth´s atmosphere could be associated to the Yarkovsky and /or YORP effects. Several works have shown that the solar radiation is able to modify asteroidal orbits and rotational periods [5, 6], and it is possible that the periodicity in the variability of this radiation be the cause of periodicities in the falling of asteroidal material observed in this work. Respect to the periodicities around 4.6 and 10.3 years, they could be related to the magnetic solar cycle. The 4.6 years periodicity could be related to Jupiter too. According to NASA (https://solarsystem.nasa.gov/planets/jupiter/overvie w/), the Jupiter orbital period is 4333 Earth days, so the ratio between this period and 1679 Earth days (̴ 4.6 year period) is almost 13/5.
Summary and Conclusions
1. The Sun could be a gravitational trigger of meteoroids from their neighborhood to Earth.
2. The periodicity around 12.7 days is possible associated with the Carrington rotation as well as the 2.5 days periodicity.
References
[1] Torrence, Ch., Compo, G. P.: A practical guide to wavelet analysis, Bulletin of American Meteorogical Society, vol. 79, No. 1, pp. 61-78, 1998. https://doi.org/10.1175/1520-0477(1998)079<0061:APGTWA>2.0.CO;2
[2] Soon, W., Dutta, K., Legates, D. R., Velasco, V., Zhang, W.: Variation in surface air temperature of China during the 20th century, J. Atmos. Sol-Terr. Phy. 73, pp. 2331-2344, 2011.
[3] Velasco Herrera, V. M., Soon, W., Velasco Herrera, G., Traversi, R., Horiuchi, K.: Generalization of the cross-wavelet function, New Astronomy, 56, pp. 86-93, 2017.
[4] Nayar, S. R. P.: Periodicites in solar activity and their signature in the terrestrial environment, ILWS Workshop 2006, Goa, India, February 19-24, pp. 1-9, 2006.
[5] Farnocchia, D., Chesley, S. R., Takahashi, Y., Rozitis, B., Vokrouhlický, D., Rush, B. P., Mastrodemos, N., Kennedy, B.M., Park, R. S., Bellerose, J., Lubey, D. P., Velez, D., Davis, A.B., Emery, J. P., Leonard, J. M., Geeraert, J., Antreasian, P.G., Lauretta, S.: Ephemeris and Hazard Assessment for Near-Earth Asteroid (101955) Bennu Based on OSIRIS-REx Data, Icarus, 369, https://doi.org/10.1016/j.icarus.2021.114594, 2021.
[6] Zegmott, T. J., Lowry, S. C., Rozek, A., Rozitis, B., Nolan, M. C., Howell, E.S., Green, S. F., Snodgrass, C., Fitzsimmons, A., Weissman, P. R.: Detection of the YORP Effect on the Contact Binary (68346) 2001 KZ66 from Combined Radar and Optical Observations, Monthly Notices of the Royal Astronomical Society. 507, pp. 4914-4932, https://doi.org/10.1093/mnras/stab2476, 2021.
How to cite: Maravilla, D., Pazos, M., and Cordero, G.: Are fireballs fall on Earth modulated by our star?, Europlanet Science Congress 2022, Granada, Spain, 18–23 Sep 2022, EPSC2022-26, https://doi.org/10.5194/epsc2022-26, 2022.
1. Introduction
The Fireball Recovery and Inter Planetary Observation Network (FRIPON) network [1] uses all-sky cameras in order to detect fireballs. The FRIPON network comprises over 150 cameras installed all over Europe [1]. In this work we focus on the results obtained by the Meteorite Orbits Reconstruction by Optical Imaging (MOROI) [2] component of the FRIPON network in Romania. As of May 2022, the MOROI network detects the events with the use of 13 all-sky cameras.
2. Methods
The method for computing the fireball trajectory used by FRIPON is presented in [3].
The height, velocity and slope γ of the meteoroid are the input data for computing the ballistic coefficient α and the mass-loss parameter β. We select the candidates that are likely to produce meteorites of the ground using the α-β algorithm presented in [4], [5], [6], [7].
3. Results
Starting from January 2021 (the starting moment of data fusion of the MOROI network into the FRIPON network) until the present time (May 2022) over 100 meteors were detected. We present the most spectacular events that are likely to result on a meteorite production on the surface of the Earth.
Figure 1: The outcome of the FRIPON (MOROI) detections in Romania
In Figure 1 are represented the coordinates of the meteoroids with noticeable deceleration in the (ln(αsinγ),lnβ) coordinates system. The values of the shape parameter correspond to the cases when the meteoroid doesn’t rotate (µ=0) or rotates uniformly (µ=2/3).
The boundaries (‘likely fall’, ‘possible fall’, ‘unlikely fall’) are represented for meteoroids with final mass of 50 g.
We processed the 100 detections of the FRIPON (MOROI) network in Romania. From this amount of data, we found 15 fireball events with noticeable deceleration. We found one event in the ‘likely fall’ area and three events in the ‘possible fall’ area. The fireball that is likely to produce meteorites was detected by the MOROI network on 24.11.2021 at 19:20:57 UT.
We model the dark flight trajectory of the meteoroids with the ‘likely fall’ and ‘possible fall’ outcomes and determine their strewn field with the model presented in [8], [9]. We use the wind model from the European Centre for Medium-Range Weather Forecasts (ECMWF).
A meteorite recovery campaign will be organised to identify the strewn field area.
Acknowledgement.
The work of IB and MB was partially supported by a grant of the Romanian Ministry of Education and Research, CNCS-UEFISCDI, project number PN-III-P1-1.1-PD-2019-0784, within PNCDI III. The work of IB, MB, AN was partially supported by a grant of the Ministry of National Education and Scientific Research, PNIII-P2-1214/25.10.2021, program no. 36SOL/2021. JM and MG acknowledge the Academy of Finland project no. 325806 (PlanetS).
References:
[1] Colas F., Zanda B., Bouley S., Jeanne S., Malgoyre A., Birlan M., Blanpain C., Gattacceca J., Jorda L., Lecubin J., et al. (385 more) FRIPON: a worldwide network to track incoming meteoroids. Astronomy &. Astrophys. 644, A53. doi:10.1051/0004-6361/202038649. 2020.
[2] Nedelcu D.A., Birlan M., Turcu V., Boaca I., Badescu O., Gornea A., Sonka A.B., Blagoi O., Danescu C., Paraschiv P. Meteorites Orbits Reconstruction by Optical Imaging (MOROI) Network. Romanian Astronomical Journal 28(1), 57 – 65. 2018.
[3] Jeanne, S., Colas, F., Zanda, B., Birlan, M., Vaubaillon, J., Bouley, S., Vernazza, P., Jorda, L., Gattacceca, J., Rault, J. L., Carbognani, A., Gardiol, D., Lamy, H., Baratoux, D., Blanpain, C., Malgoyre, A., Lecubin, J., Marmo, C., Hewins, P. Calibration of fish-eye lens and error estimation on fireball trajectories: application to the FRIPON network. Astronomy and Astrophysics, 627:A78. 2019.
[4] Gritsevich, M. I. The Pribram, Lost City, Innisfree, and Neuschwanstein falls: An analysis of the atmospheric trajectories. Solar System Research.42, 372–390. 2008.
[5] Gritsevich, M.I., Stulov, V.P., Turchak, L.I. Consequences of collisions of natural cosmic bodies with the Earth's atmosphere and surface. Cosmic Research vol.50, no.1, 56-64. 2012.
[6] Sansom, E.K., Gritsevich, M., Devillepoix, H.A.R., Jansen-Sturgeon, T., Shober, P.,
Bland, P.A., Towner, M.C., Cupák, M., Howie, R.M., Hartig, B.A.D. Determining Fireball Fates Using the α-β Criterion. Astrophysical Journal 885(2):115. 2019.
[7] Boaca I., Gritsevich M., Birlan M., Nedelcu, A., Boaca, T., Colas, F., Malgoyre, A.,
Zanda, B., Vernazza P., to be submitted. 2022.
[8] Moilanen, J., Gritsevich, M., Lyytinen, E., Determination of strewn fields for meteorite falls, Monthly Notices of the Royal Astronomical Society 503, 3337–3350. 2021.
[9] Boaca I., Nedelcu A., Birlan M., Boaca T., Anghel S. Mathematical model for the dark-flight trajectory of a meteoroid, Romanian Astronomical Journal, Vol. 31, No. 2. 2021.
How to cite: Boaca, I. L., Moilanen, J., Gritsevich, M., Birlan, M., Nedelcu, A., Boaca, T., Colas, F., Malgoyre, A., Zanda, B., and Vernazza, P.: Analysis of the meteorite-producing fireballs registered by the MOROI component of the FRIPON network, Europlanet Science Congress 2022, Granada, Spain, 18–23 Sep 2022, EPSC2022-160, https://doi.org/10.5194/epsc2022-160, 2022.
Introduction
Meteorites offer large quantities of interesting and useful information regarding the formation of the Earth, the Solar System and maybe the life, but for their study, they have to be found first. This is not an easy task since these objects only glow in the upper layers of the atmosphere and after that, there is no information about their locations. Our project aims to model this phase of meteor flight, the so-called ‘dark flight’, and gather as much information about it as possible, regarding the meteors’ location, velocity, etc.
In Hungary Dr Tibor Hegedüs and his high-altitude balloon team (called DAMBALL) released the task to simulate the dark flight of meteoroids by ‘artificial meteoroid’ bodies, which have their own telemetry. A part of our group (‘Soprobotics’) has developing and programming such compact data-collecting devices that can be inserted in small spheres, the falling trajectories of which would be analogous to a meteor in the phase of dark flight. These units were named Info-Droplets. When creating the droplets, the main concept was keeping them as small as possible. The desirable size were defined within the range of D=5-10 cm
Hardware
The Droplets’ main components
Control of one device is fulfilled by a WEMOS D1 mini pro microcontroller. The most important tool of the position measurement is a GPS module, this supplies the data required by the observing team. The collected data are stored on a SD card which has its own shield. The unit is powered by a 3.7V LiPo battery.
Evolution of the Droplets’ design
Mk 1:
This first device was consisted only one microcontroller, an SD-Card shield and an OCTOPART GPS which was provisionally connected with wires. This GPS works up to an altitude of 18 km due to a built-in limitation and thus it was insufficient for our purposes.
Mk 2:
The GPS was replaced by a UBLOX-NEO-M8Q which does not have the previously mentioned height limitation. This was planted on a custom PCB.
For the additional functionality of Droplet-Droplet and Droplet-Ground communication, a LoRa RFM 95W radio module was added. This offers help in finding the droplets after the flight and supplies a log of measured data in case a unit should be lost or destroyed.
Mk 3:
Further test flights revealed potential improvements which were duly implemented.
A new, active GPS antenna was added, the GPS shield was redesigned placing the LoRa on it as well and adding a port for the GPS antenna and a battery-control shield was added for constant supply-voltage and charging capabilities.
Software
We programmed the microcontrollers in the Arduino IDE. For the GPS we used the TinyGPS++ library and the radio modules had their own library. This did not support the ESP based boards, but we could modify it, so the two devices could work together.
The data collected during the fall are easily importable to Excel.
Code structure:
Upon turning on the droplet we are running the setup. Here we are starting every module (SD card, Radio, Gps).
In the main loop we are reading the GPS and storing the data on the card. Then the communication starts via radio with the other droplets, and with the Earth unit as well.
Setup:
In the setup procedure, several fundamental things are started.
Some basic information, we have :
GPS communication pins, droplet ID, droplet version, software version, etc.
Finally, we are starting the radio and the GPS. Both modules are using SPI, we can select the one we are using through its chip selector pin.
Main loop:
Firstly, we are measuring the position of the unit by the GPS and saving it in the data variable. This includes the droplet ID, the number of satellites, time, latitude, longitude and the altitude.
For safety purposes we write the same data into two files simultaneously.
The first part of the communication is the sending of the data variable to the other droplet and to the Earth unit. The second part is the receiving and saving the data acquired from the other droplets.
Additional features:
If the GPS loses its signal, the droplet detects this and restarts.
We can also send some commands to the droplet via radio from the Earth unit.
We can restart the whole device, the GPS, the radio, and get the file version and wipe the whole SD card remotely.
Test flights and results
The high-altitude balloons can carry the Droplets to a height of about or more then 30 km where they blow up. The gondola, and the previously separated Droplets fall to the ground (the gondola is with a parachute and the Droplets are by a free-fall)
August 2018: Droplets Mk 1
From the data logs it was apparent that both the climb and the fall was well documented, but the part of the flight above 18000m altitude is missing owing to the GPS’s built in limitation.
September 2019: Droplets Mk 2
The first flight, where we used radio communication, but the flight data was corrupted and could not be evaluated.
June 2020: Droplets Mk 2
The horizontal part of the graph is not caused by the altitude cutoff as the UBLOX GPS was used, but the GPS modules crashed and the satellite communication was severed. Although radio communication between Droplets and the Ground unit was active, we could not solve the problem at that time.
Sadly no further test flights could be conducted to date because of the COVID 19 pandemic, thus the Droplets could not be built into their spherical housings and dropped separately from the gondola to be perfect meteor-models.
Summary and conclusions
Three successful test flights were conducted and the graphs show that our Droplets – which became quite more complex in the meantime, than our concept at the start of the project – work satisfactorily and the balloon team can use them for the original task at hand. The final test flight and the actual missions are planned for this summer.
How to cite: Bejó, M., Hegedűs, T., Hargitai, B., Molnár, B., Sztojka, Á., and Lang, Á.: Modelling the fall of meteors during the dark flight with Info-Droplets, Europlanet Science Congress 2022, Granada, Spain, 18–23 Sep 2022, EPSC2022-900, https://doi.org/10.5194/epsc2022-900, 2022.