3D meteoroid trajectories

Sansom, Eleanor K.; Jansen‐Sturgeon, Trent; Rutten, Mark; Devillepoix, Hadrien A. R.; Bland, P. A.; Howie, Robert M.; Cox, M. A.; Towner, M. C.; Cupák, Martin; Hartig, Benjamin A. D.

doi:10.1016/j.icarus.2018.09.026

Cited by 25 publications

(22 citation statements)

References 29 publications

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“…For accurate orbital measurements we strongly suggest installation of more precise all-sky systems with angular resolutions approaching or exceeding one arc-minute per pixel so that the velocity accuracy of less than 0.1 km s −1 can be achieved, as recommended by Granvik & Brown (2018). We show that compensation for trajectory bending due to gravity should be taken into account for longer fireballs (> 4 seconds) due to its significant influence on the radiant accuracy, as noted earlier by Ceplecha (1979) and Sansom et al (2019).…”

Section: Resultssupporting

confidence: 68%

Estimating trajectories of meteors: an observational Monte Carlo approach – II. Results

Vida

Brown

Campbell-Brown

et al. 2019

Monthly Notices of the Royal Astronomical Society

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In the first paper of this series we examined existing methods of optical meteor trajectory estimation and developed a novel method which simultaneously uses both the geometry and the dynamics of meteors to constrain their trajectories. We also developed a simulator which uses an ablation model to generate realistic synthetic meteor trajectories which we use to test meteor trajectory solvers. In this second paper, we perform simulation validation to estimate radiant and velocity accuracy which may be achieved by various meteor observation systems as applied to several meteor showers.For low-resolution all-sky systems, where the meteor deceleration is generally not measurable, the multi-parameter fit method assuming a constant velocity better reproduces the radiant and speed of synthetic meteors. For moderate field of view systems, our novel method performs the best at all convergence angles, while multi-parameter fit methods generally produce larger speed errors. For high-resolution, narrow field of view systems, we find our new method of trajectory estimation reproduces radiant and speed more accurately than all other methods tested. The ablation properties of meteoroids are commonly found to be the limiting factor in velocity accuracy.We show that the true radiant dispersion of meteor showers can be reliably measured with moderate field of view (or more precise) systems provided appropriate methods of meteor trajectory estimation are employed. Finally, we compare estimated and real angular radiant uncertainty and show that for the solvers tested the real radiant error is on average underestimated by a factor of two.

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Section: Resultssupporting

confidence: 68%

Estimating trajectories of meteors: an observational Monte Carlo approach – II. Results

Vida

Brown

Campbell-Brown

et al. 2019

Monthly Notices of the Royal Astronomical Society

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“…This does require assumptions to be made for density, shape and of course µ. For a more in depth analysis/assessment of specific meteoroid trajectories, more involved modelling techniques such as Sansom et al (2019) and Egal et al (2017) can now be applied with confident use of resources.…”

Section: Discussionmentioning

confidence: 99%

Determining Fireball Fates Using the α–β Criterion

Sansom

Gritsevich

Devillepoix

et al. 2019

ApJ

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As fireball networks grow, the number of events observed becomes unfeasible to manage by manual efforts. Reducing and analysing big data requires automated data pipelines. Triangulation of a fireball trajectory can swiftly provide information on positions and, with timing information, velocities. However, extending this pipeline to determine the terminal mass estimate of a meteoroid is a complex next step. Established methods typically require assumptions to be made of the physical meteoroid characteristics (such as shape and bulk density). To determine which meteoroids may have survived entry there are empirical criteria that use a fireball's final height and velocity -low and slow final parameters are likely the best candidates. We review the more elegant approach of the dimensionless coefficient method. Two parameters, α (ballistic coefficient) and β (mass-loss), can be calculated for any event with some degree of deceleration, given only velocity and height information. α and β can be used to analytically describe a trajectory with the advantage that they are not mere fitting coefficients; they also represent the physical meteoroid properties. This approach can be applied to any fireball network as an initial identification of key events and determine on which to concentrate resources for more in depth analyses. We used a set of 278 events observed by the Desert Fireball Network to show how visualisation in an α -β diagram can quickly identify which fireballs are likely meteorite candidates.

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“…After having analysed five long fireballs, these authors conclude that it is not possible to detect the meteor curvature from all-sky images. There are some exceptions, such as the two cases described by Sansom et al (2019). If such bolides are observed by the FRIPON network, they will need to be reduced by a particular method, and not by the regular automatic method described here.…”

Section: Straight-line Trajectoriesmentioning

confidence: 98%

“…Typical median timing accuracy is about 20 ms (Barry et al 2015), but it can be worse if the internet connection is off, and the computer therefore depends on its internal clock for timing. As a result, the camera acquisitions are not synchronised as those of Desert Fireball Network are (Sansom et al 2019). This lack of temporal accuracy combined with the high speed of the meteors prevents us from computing their positions by a direct triangulation as in Sansom et al (2019), hence we have not directly computed the position of the meteor as a function of time as Gural (2012) does.…”

Section: Trajectoriesmentioning

confidence: 99%

“…As a result, the camera acquisitions are not synchronised as those of Desert Fireball Network are (Sansom et al 2019). This lack of temporal accuracy combined with the high speed of the meteors prevents us from computing their positions by a direct triangulation as in Sansom et al (2019), hence we have not directly computed the position of the meteor as a function of time as Gural (2012) does. Instead, we computed its trajectory assuming a straight-line after Ceplecha (1987).…”

Section: Trajectoriesmentioning

confidence: 99%

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Calibration of fish-eye lens and error estimation on fireball trajectories: application to the FRIPON network

Jeanne

Colas

Zanda

et al. 2019

A&A

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Context. Fireball networks are developing over the whole planet, with the aim of recovering meteorites and at the same time determining their orbits. The ultimate goal of such networks is to identify the parent bodies of meteorite families to achieve this, orbit accuracy is critical. Yet, the determination of an orbit relies on a long and complex reduction process including: (1) astrometry, with heavy distortion for fish-eye lenses, (2) estimation of the external bias on the observation, (3) fit of the trajectory, (4) deceleration model, and (5) actual orbit computation. Aims. Our goal is to compute accurate trajectories with an estimate of internal and external errors as realistic as possible, taking advantage of the dense observation network FRIPON (Fireball Recovery and InterPlanetary Observation Network), which comprises more than 100 cameras in France and Europe. In particular, we pay special attention to the distortion of images due to fish-eye lenses. In the present paper, we describe the analytical protocol that allows us to compute trajectories and their uncertainties. Methods. We developed a general distortion model to be used on the FRIPON fish-eye cameras. Such a model needs to be accurate even at low elevation, as most fireball observations are performed low on the horizon. The radial distortion is modelled by a nine-degree odd polynomial, hence by five parameters. In addition, we used three parameters to describe the geometry of the camera and two for non-symmetrical distortion. Lastly, we used a new statistical method taking systematic errors into account, which allows us to compute realistic confidence intervals. We tested our method on a fireball that fell on 2017-08-94 UT 00:06. Results. The accuracy of our astrometrical model for each camera is 2 arcmin (1σ), but the internal error on the fireball of 2017-08-94 UT 00:06 measurement is 0.7 arcmin (better than 1/10 pixel). We developed a method to estimate the external error considering that each station is independent and found it equal to 0.8 arcmin. Real residuals are coherent with our estimation of internal and external error for each camera, which confirms the internal consistency of our method. We discuss the advantages and disadvantages of this protocol.

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3D meteoroid trajectories

Cited by 25 publications

References 29 publications

Estimating trajectories of meteors: an observational Monte Carlo approach – II. Results

Estimating trajectories of meteors: an observational Monte Carlo approach – II. Results

Determining Fireball Fates Using the α–β Criterion

Calibration of fish-eye lens and error estimation on fireball trajectories: application to the FRIPON network

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