A practical re-weighting scheme of data fitting: application to asteroids orbit determination with Gaia
Dmitri. E. Vavilov, Ziyu. Liu, Daniel. Hestroffer, Josselin. Desmars

TL;DR
The paper introduces a simple reweighting scheme for weighted least squares that improves asteroid orbit determination by effectively handling heterogeneous observational uncertainties, especially with Gaia data.
Contribution
It presents a practical, three-step reweighting method to enhance the consistency and accuracy of parameter estimation in the presence of mixed-precision data.
Findings
Reweighted solutions better match older data for several asteroids.
Increasing Gaia observation uncertainties improves fit quality, highlighting systematic biases.
Reweighting reduces impact probability estimates for near-Earth asteroid 2024 YR4.
Abstract
The method of weighted least squares is widely used in parameter estimation problems such as asteroid orbit determination. A key difficulty is the treatment of observational uncertainties, especially when combining heterogeneous datasets with differing precision. We propose a simple reweighting scheme that adjusts the contribution of each measurement group to ensure a statistically consistent least-squares solution. It consists of three steps: (i) estimating error standard deviations for each observational subset, (ii) rescaling their weights by the corresponding variances, and (iii) a weighted least-squares fit with the adjusted weights. We apply this to heliocentric orbit fitting of asteroids using ground-based astrometry and high-precision Gaia measurements. We validated the method by fitting each orbit to a restricted set and comparing with the complete set of measurements. For 7…
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