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Drolshagen, E., et al., [Context] The luminous efficiency, τ, can be used to compute the pre-Atmospheric masses of meteoroids from corresponding recorded meteor brightnesses. The derivation of the luminous efficiency is non-Trivial and is subject to biases and model assumptions. This has led to greatly varying results in the last decades of studies. [Aims] The present paper aims to investigate how a reduction in various observational biases can be achieved to derive (more) reliable values for the luminous efficiency. [Methods] A total of 281 meteors observed by the Fireball Recovery and InterPlanetary Observation Network (FRIPON) are studied. The luminous efficiencies of the events are computed using an ablation-based model. The relations of τ as a function of the pre-Atmospheric meteoroid velocity, ve, and mass, Me, are studied. Various aspects that could render the method less valid, cause inaccuracies, or bias the results are investigated. On this basis, the best suitable meteors were selected for luminous efficiency computations. [Results] The presented analysis shows the limits of the used method. The most influential characteristics that are necessary for reliable results for the τ computation were identified. We study the dependence of τ on the assumed meteoroid's density, ρ, and include improved ρ-values for objects with identified meteoroid stream association. Based on the discovered individual biases and constraints we create a pre-debiased subset of 54 well-recorded events with a relative velocity change >80%, a final height

Context. Several fireball networks deploy all-sky cameras for the observation of bright meteors and bolides. Because the field is heavily distorted, a dedicated astrometric reduction is needed. A precise computation of the astrometric solution is essential to determine reliable orbital elements of the parent body and to recover possible fragments on ground.Aims. The purpose of this article is to assess the astrometric performances of this type of instruments, which is characterized by a wide field of view and small apertures. The currently available parametric models show a high level of complexity and generally suffer from parameter crosstalk and local minimum confinement if the initial estimates are not precisely provided. We address these issues here and propose a solution by adopting a new explicit parametrisation.Methods. The mismatch between the optical axis and the local zenith direction requires a geometric description that includes two centres of symmetry that lie very close to each other on the focal plane, causing an unreliable estimate of the related parameters. The introduction of new physical coordinates overcomes these issues, allowing a direct and independent estimation. We assessed the performances of different centroiding algorithms in the experimental conditions of an undersampled point spread function of reference stars and saturated bolides on video records. We implemented the algorithm for an automatic identification of bright sources on calibration frames and subsequent correlation with catalogue positions using astrometric projections of increasing complexity.Results. The algorithm and the new parametrisation of the astrometric solution are tested against real data from the PRISMA Italian fireball network and ensure good convergence properties for all cameras we tested so far. By processing astrometric data with a few months’ statistics, we can achieve a random projection indeterminacy of the order of 10 arcsec, which is negligible with respect to single measurement errors on the bolide position.

Algorithms aimed at the evaluation of critical quantities are based on models with many parameters, which values are estimated from data. The knowledge, with high accuracy, of these values and the control of their temporal evolution are important features. In this work, we focus on the latter subject, and we show a proposed pipeline for the BAM (Basic Angle Monitoring) Long Term Analysis, aimed at the study of the calibration parameters of the BAM device and of the Basic Angle variation, searching for unwanted trends, cyclic features, or other potential unexpected behaviours.