Observing meteors by creating artificial luminous clouds in the Earth’s atmosphere

В статье дается предварительная теоретическая оценка возможности применения нового способа наблюдения метеоров в атмосфере Земли с помощью искусственных светящихся облаков. При попадании метеоров в такие облака, образованные веществом с потенциалом ионизации в несколько раз меньшем потенциала ионизации атмосферных газов, происходит быстрая ионизация реагента облака за счет термического и ударного воздействия метеорного тела, приводящая к увеличению светимости метеорных следов. Предполагается, что такой эффект будет способствовать увеличению яркости слабых метеоров, находящихся на пороге обнаружения современных телевизионных камер. Это позволит проводить исследования метеоров и метеорных потоков, доступных ранее только радиолокационными методами наблюдения. The article provides a preliminary theoretical assessment of the possibility of using a new method of observing meteors in the Earth’s atmosphere using artificial luminous clouds. When meteors hit such clouds formed by a substance with an ionization potential several times lower than the ionization potential of atmospheric gases, the cloud reagent is rapidly ionized due to the thermal and impact effects of the meteor body, which leads to an increase in the luminosity of meteor tracks. It is assumed that this effect will increase the brightness of weak meteors, which are on the threshold of detection by modern TV cameras. This will make it possible to conduct studies of meteors and meteor showers that were previously available only by radar observation methods.

Meteor shower radiant dispersions in Global Meteor Network data

ABSTRACT Meteor showers occur when streams of meteoroids originating from a common source intersect the Earth. There will be small dissimilarities between the direction of motion of different meteoroids within a stream, and these small differences will act to broaden the radiant, or apparent point of origin, of the shower. This dispersion in meteor radiant can be particularly important when considering the effect of the Earth’s gravity on the stream, as it limits the degree of enhancement of the stream’s flux due to gravitational focusing. In this paper, we present measurements of the radiant dispersion of 12 showers using observations from the Global Meteor Network. We find that the median offset of individual meteors from the shower radiant ranges from 0.32○ for the eta Aquariids to 1.41○ for the Southern Taurids. We also find that there is a small but statistically significant drift in Sun-centred ecliptic radiant and/or geocentric speed over time for most showers. Finally, we compare radiant dispersion with shower duration and find that, in contrast with previous results, the two quantities are not correlated in our data.

On the detectability of the meteor pairs created by fragmentation in near-Earth space

<p>Although numerous observers reported that meteors appear in pairs or groups, recent papers based on instrumental observations did not confirm such results. At least, among older meteor showers such grouping was not confirmed. On the other hand, among younger streams, such behaviour is still possible.</p> <p>In our recent paper dedicated to the search of pairs among Geminid meteors, we found that we have no evidence for the physically connected pairs despite the fact that a number of potential candidates have been detected. Monte Carlo statistical test showed that all the cases can be results of coincidental approaches of the particles in a similar space and time.</p> <p>Therefore, we prepared a model of orbital fragmentation of meteoroids in the vicinity of the Earth, which follows trajectories of fragmented particles ejected with different velocities in different directions under  the solar radiation pressure. The collisions with interplanetary particles as the possible source of the pairs are taken into account for the major meteor showers during whole year. </p> <p>The paper will provide constraints on the time of ejection, ejection velocities and ejection angles, which will allow the pairs or groups to be detected in the Earth atmosphere by the video or photographic cameras.</p>

It's a Bird it's a Plane it's a Meteor

<p>Meteor showers are some of the most dazzling and memorable events occuring in the night sky. Caused by bits of celestial debris from comets and asteroids entering Earth’s atmosphere at astronomical speeds, meteors are bright streaks of light in the night sky, sometimes called shooting stars. Those meteors are recorded, tracked and triangulated by low-light surveillance cameras in a project called CAMS: Cameras for Allsky Meteor Surveillance. CAMS offers insights into a universe of otherwise invisible solar system bodies, but that task has proven difficult due to the lack of automated supervision. Until recently, much of the data control was done by hand. Necessary to build supervised classification models,  labeled training data is essential because other man-made objects such as airplanes and satellites can be mistaken for meteors. To address this issue, we leverage one year's worth of meteor activity data from CAMS to provide weak supervision for over a decade of collected data, drastically reducing the amount of manual annotation necessary and expanding available labelled meteor training data.</p><p> </p><p>Founded in 2010, CAMS aims to automate video surveillance of the night sky to validate the International Astronomical Union’s Working List of Meteor Showers, discover new meteor showers, and predict future meteor showers. Since 2010, CAMS has collected a decade's worth of night sky activity data in the form of astrometric tracks and brightness profiles, a year of which has been manually annotated. We utilize this one year's labelled data to train a high confidence LSTM meteor classifier to generate low confidence labels for the remaining decade’s worth of meteor data. Our classifier yields confidence levels for each prediction, and when the confidence lies above a statistically significant threshold, predicted labels can be treated as weak supervision for future training runs. Remaining predictions below the threshold can be manually annotated. Using a high threshold minimizes label noise and ensures instances are correctly labeled while considerably reducing the  amount of data that needs to be annotated. Weak supervision can be confirmed by checking date ranges and data distributions for known meteor showers to verify predicted labels.</p><p> </p><p>To encourage discovery and distribution of training data and models, we additionally provide scripts to automate data ingestion and model training from raw camera data files. The data scripts handle processing of CAMS data, providing a pipeline to encourage open sharing and reproduction of our research. Additionally, we provide code for a LSTM classifier baseline model which can identify probable meteors. This baseline model script allows further exploration of CAMS data and an opportunity to experiment with other model types.  </p><p> </p><p>In conclusion, our contributions are (1) a weak supervision method utilizing a year’s worth of labelled CAMS data to generate labels for a decade’s worth of data, along with (2) baseline data processing and model scripts to encourage open discovery and distribution. Our unique contributions expand access to labeled training meteor data and make the data globally and publicly accessible thorough daily generated maps of meteor shower activity posted at http://cams.seti.org/FDL/. </p>