Abstract Fast sampling photometry is a key observable for characterising fireballs, particularly their fragmentation episodes, which are strongly connected to the internal structure of the meteoroid and its physical properties. Accurate photometric measurements remain a challenge due to the large dynamic range required (upwards of 10 stellar magnitudes), driving operational complexity and cost. We have developed a system using an all-sky camera operating at up to 500 frames per second, featuring a novel implementation of Detection Localised Auto-brightness Control. The large data throughput is managed by custom software that performs transient detection, region-of-interest saving, and real-time photometry. We present results from two field deployments: the first validates the system’s photometric accuracy against conventional 30 frames per second cameras, while the second demonstrates the successful implementation of Detection Localised Auto-brightness Control in capturing a bright, magnitude -15 fireball with minimal saturation. With the Detection Localised Auto-brightness Control, the system achieves an effective dynamic range between apparent magnitudes of approximately -3 to -17, allowing it to capture light curves with minimal saturation for most fireballs, excluding rare superbolides. The resulting high-quality light curve enabled a successful semi-empirical fragmentation analysis verifying the system’s ability to provide data for detailed physical modelling. The primary application for this validated system will be as a core component of the Global Fireball Observatory’s next-generation instrumentation. The intention is to deploy it in a hybrid observatory, operating alongside a dedicated high-resolution astrometric camera. This configuration will allow the network to simultaneously capture precise trajectory data for orbit and fall-line calculations and acquire complete, unsaturated high dynamic range light curves at high temporal resolution for detailed physical analysis, combining the strengths of both systems.
Giancono et al. (Mon,) studied this question.