A new three-point inverse solution using the α-β model reconstructs meteoroid masses and bulk densities from limited fireball observations, achieving 88% convergence on the EN catalog and producing a continuous density range of 300-4000 kg m^{-3} instead of discrete PE categories.
Analysis of orbital and physical properties of centimeter-sized meteoroids
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Machine learning clustering of meteor observations produces a new hardness classification H_class that refines traditional Kb models using more parameters and reveals compositional structure in meteoroid populations.
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Consistency between dynamical modeling and photometrically derived masses of fireballs
A new three-point inverse solution using the α-β model reconstructs meteoroid masses and bulk densities from limited fireball observations, achieving 88% convergence on the EN catalog and producing a continuous density range of 300-4000 kg m^{-3} instead of discrete PE categories.
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A Machine Learning Approach to Meteor Classification
Machine learning clustering of meteor observations produces a new hardness classification H_class that refines traditional Kb models using more parameters and reveals compositional structure in meteoroid populations.