Characterising Fireballs for Mass Determination: Steps Toward Automating the Australian Desert Fireball Network
E. K. Sansom1, P. A. Bland1, J. Paxman2, M. C. Towner1
1Department of Applied Geology, Curtin University, GPO Box U1987, Perth, WA 6845, Australia. [email protected]; [email protected]; m. [email protected]
2Department of Mechanical Engineering, Curtin University, GPO Box U1987, Perth, WA 6845, Australia. [email protected].
Abstract
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 km2. 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.
1. Introduction
Analysis of meteorites can lead to valuable insights into the formation of the proto-planetary disk within which their parent asteroids were created. Without a constraint on a meteorite’s origin in the Solar System, interpreting its unique geological record can be extremely difficult. The recording of fireball phenomena can enable the reconstruction of orbits and has the potential to lead to the recovery of fresh meteorites. This objective has been the driver for a number of dedicated fireball camera network projects dating back to the late 1950s [2]. Such camera networks optically photograph fireballs with the aim of extracting orbital information and estimating potential fall locations. These camera networks have led to the recovery of 10 meteorites, including two by the Desert Fireball Network (DFN) in Australia during its trial phase [3][1]. Over the next few months, the DFN will establish over 50 new camera stations to expand its coverage to an area in excess of 2 million km2. This will make it the largest fireball network in history, and consequently there is a need for automated systems of data analysis. Determining meteorite fall sites from networked observations relies on characterising meteoroids as they pass through the atmosphere. This process is complicated by a significant number of unknown variables. In addition, in the case of the DFN, very large data volumes will need to be reduced. The current work addresses both of these issues.
There have been two previous approaches to analysing optical image data for mass determination: the photometric method and the dynamic method. The photometric method uses the luminosity of the fireball as a proxy for ablated mass. Since this concept was established by Öpik in 1933 [4] , it has become recognised as the preferred method. This approach however gives unreliable meteoroid entry masses in many cases [5] and is based on ideas of hypersonic aerodynamics that are now out-of-date [5].
The dynamic method uses ballistic equations of flight through the atmosphere to calculate mass from deceleration. In the past this approach was limited by the accuracy of measurements that could be interpreted from photographic plates [2]. Difficulties with this method are also due to the unknown characteristics of the meteoroid such as density and shape that are required for the dynamic calculation. Recent work by [6] has enabled the application of an analytical solution by
978-1-4673-5225-3/14/$31.00 ©2014 IEEE combining these unknown parameters into two dimensionless constants. This has been applied by Gritsevich [7][8] to the Canadian MORP network datasets. This enables a good model fit to the data but later requires assumptions of these same meteoroid characteristics in order to determine mass.
Given the limitations of these established techniques, a new method is presented here. It involves a multi-step approach and is based on the dynamic method; using the same equations. An initial dynamic optimisation stage determines the combination of meteoroid characteristics that will allow a fit to the data. This is then followed by an extended Kalman filter to incorporate the data into the model. The final goal will be to enable the automation of meteoroid mass determination for the DFN to enable the rapid recovery of meteorites. 2. Model
The dynamic equations used for ballistic entry through the atmosphere from [6] are: