Characterising fireballs for mass determination: Steps toward automating the Australian desert fireball network

Determining the mass of a meteoroid passing through the Earth's atmoshphere is essential to determining potential meteorite fall positions. This is only possible if the characteristics of these meteoroids, such as density and shape are in some way constrained. When a meteoroid falls through the atmosphere, it produces a bright fireball. Dedicated camera networks have been established to record these events with the objectives of calculating orbits and recovering meteorites. The Desert Fireball Network (DFN) is one of these programs and will eventually cover ~2 million km
²
. Automated observatories take high-resolution optical images throughout the night with the aim of tracking and recovering meteorites. From these optical images, the position, mass and velocity of the meteoroid at the end of it's visible trajectory is required to predict the path to the ground. The method proposed here is a new aproach which aims to automate the process of mass determination for application to any trajectory dataset, be it optical or radio. Two stages are involved, beginning with a dynamic optimisation of unknown meteoroid characteristics followed by an extended Kalman filter. This second stage estimates meteoroid states (including position, velocity and mass) by applying a prediction and update approach to the raw data and making use of uncertainty models. This method has been applied to the Bunburra Rockhole dataset, and the terminal bright flight mass was determined to be 0.412 ±0.256 kg, which is close to the recovered mass of 338.9 g [1]. The optimal entry mass using this proposed method is 24.36 kg, which is consistent with other work based on the estabished photometric method and with cosmic ray analysis. The new method incorporates the scatter of the raw data as well as any potential fragmentation events and can form the basis for a fully automated method for characterising mass and velocity.