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Register a new userAnalysing Meteoroid Flights Using Particle Filters
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Fireball observations from camera networks provide position and time information along the trajectory of a meteoroid that is transiting our atmosphere. The complete dynamical state of the meteoroid at each measured time can be estimated using Bayesian filtering techniques. A particle filter is a novel approach to modelling the uncertainty in meteoroid trajectories and incorporates errors in initial parameters, the dynamical model used and observed position measurements. Unlike other stochastic approaches, a particle filter does not require predefined values for initial conditions or unobservable trajectory parameters. The Bunburra Rockhole fireball (Spurny et al. 2012), observed by the Australian Desert Fireball Network (DFN) in 2007, is used to determine the effectiveness of a particle filter for use in fireball trajectory modelling. The final mass is determined to be $2.16pm1.33, kg$ with a final velocity of $6030pm216, m,s^{-1}$, similar to previously calculated values. The full automatability of this approach will allow an unbiased evaluation of all events observed by the DFN and lead to a better understanding of the dynamical state and size frequency distribution of asteroid and cometary debris in the inner solar system.
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We present a deep learning, computer vision algorithm constructed for the purposes of identifying and classifying charged particles in camera image sensors. We apply our algorithm to data collected by the Distributed Electronic Cosmic-ray Observatory (DECO), a global network of smartphones that monitors camera image sensors for the signatures of cosmic rays and other energetic particles, such as those produced by radioactive decays. The algorithm, whose core component is a convolutional neural network, achieves classification performance comparable to human quality across four distinct DECO event topologies. We apply our model to the entire DECO data set and determine a selection that achieves $ge90%$ purity for all event types. In particular, we estimate a purity of $95%$ when applied to cosmic-ray muons. The automated classification is run on the public DECO data set in real time in order to provide classified particle interaction images to users of the app and other interested members of the public.
A signal processing method designed for the detection of linear (coherent) behaviors among random fluctuations is presented. It is dedicated to the study of data recorded from nonlinear physical systems. More precisely the method is suited for signals having chaotic variations and sporadically appearing regular linear patterns, possibly impaired by noise. We use time-frequency techniques and the Fractional Fourier transform in order to make it robust and easily implementable. The method is illustrated with an example of application: the analysis of chaotic trajectories of advected passive particles. The signal has a chaotic behavior and encounter Levy flights (straight lines). The method is able to detect and quantify these ballistic transport regions, even in noisy situations.
Based on telescopic observations of Jupiter-family comets (JFCs), there is predicted to be a paucity of objects at sub-kilometre sizes. However, several bright fireballs and some meteorites have been tenuously linked to the JFC population, showing metre-scale objects do exist in this region. In 2017, the Desert Fireball Network (DFN) observed a grazing fireball that redirected a meteoroid from an Apollo-type orbit to a JFC-like orbit. Using orbital data collected by the DFN, in this study, we have generated an artificial dataset of close terrestrial encounters that come within $1.5$ lunar distances (LD) of the Earth in the size-range of $0.01-100$kg. This range of objects is typically too small for telescopic surveys to detect, so using atmospheric impact flux data from fireball observations is currently one of the only ways to characterise these close encounters. Based on this model, we predict that within the considered size-range $2.5times 10^{8}$ objects ($0.1%$ of the total flux) from asteroidal orbits ($T_{J}>3$) are annually sent onto JFC-like orbits ($2<T_{J}<3$), with a steady-state population of about $8times 10^{13}$ objects. Close encounters with the Earth provide another way to transfer material to the JFC region. Additionally, using our model, we found that approximately $1.96times 10^{7}$ objects are sent onto Aten-type orbits and $sim10^{4}$ objects are ejected from the Solar System annually via a close encounter with the Earth.
Meteoroid modelling of fireball data typically uses a one dimensional model along a straight line triangulated trajectory. The assumption of a straight line trajectory has been considered an acceptable simplification for fireballs, but it has not been rigorously tested. The unique capability of the Desert Fireball Network (DFN) to triangulate discrete observation times gives the opportunity to investigate the deviation of a meteoroids position to different model fits. Here we assess the viability of a straight line assumption for fireball data in two meteorite-dropping test cases observed by the Desert Fireball Network (DFN) in Australia -- one over 21 seconds (textit{DN151212_03}), one under 5 seconds (textit{DN160410_03}). We show that a straight line is not valid for these two meteorite dropping events and propose a three dimensional particle filter to model meteoroid positions without any straight line constraints. The single body equations in three dimensions, along with the luminosity equation, are applied to the particle filter methodology described by citet{Sansom2017}. Modelling fireball camera network data in three dimensions has not previously been attempted. This allows the raw astrometric, line-of-sight observations to be incorporated directly. In analysing these two DFN events, the triangulated positions based on a straight line assumption result in the modelled meteoroid positions diverging up to $3.09, km$ from the calculated observed point (for textit{DN151212_03}). Even for the more typical fireball event, textit{DN160410_03}, we see a divergence of up to $360$,m. As DFN observations are typically precise to $<100$,m, it is apparent that the assumption of a straight line is an oversimplification that will affect orbit calculations and meteorite search regions for a significant fraction of events.
This is an overview of recent research on meteors and the parent bodies from which they are produced. While many meteor showers result from material ejected by comets, two out of the three strongest annual showers (the Geminids and the Quadrantids) are associated with objects whose physical properties are apparently those of asteroids. In the last decades dynamical and observational studies have confirmed the existence of a number of Asteroid-Meteoroid Complexes, comprising streams and several macroscopic, split fragments. Spectroscopy of meteor showers has been utilized to investigate the perihelion-dependent thermal alteration while in interplanetary space. In this chapter, we review characteristics of the complexes, including those of some minor streams. The scientific interest is to trace the physical and dynamical properties of the complexes back to the evolutionary pathways to learn about the variety of production processes of meteoroids to form streams. We also discuss open questions in the field for the next decade.
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