Characterising the space-object population in Highly Elliptical Orbits (HEO) is key to improving our understanding of a region that remains comparatively underexplored. Current debris environment models cover the HEO regime and provide flux and spatial-density estimates. However, this regime remains less described than LEO and GEO, particularly with respect to orbital dynamics characterization, population completeness, and the validation of small-debris distributions at high apogee. As a test case to improve our understanding of the HEO regime, this work presents a Molniya case study. Building on an analysis of the catalogued population, its temporal evolution and the current modelling of this orbital regime, this paper presents a statistical search method for uncatalogued Resident Space Objects (RSOs). The approach couples a dedicated survey strategy with a Stare-and-Chase concept. The population analysis focuses on Molniya-like orbits and defines the orbital selection parameters adopted for the survey. Observations are conducted from the Northern Hemisphere, where the apogees of a significant fraction of Molniya objects cluster because of orbital geometry. At the same time, the currently catalogued population occupies orbits with apogees above the Southern-Hemisphere (at least the 60%). The survey strategy clusters the apogee distribution to identify sky regions with the highest probability of containing uncatalogued objects. Sixteen high-density apogee clusters are derived from the known Molniya population, eight in each hemisphere; the eight Northern-Hemisphere clusters are accessible to the observing site used in this work. The most observable region is then selected, and a mosaic field-of-view grid is designed and optimized by accounting for the expected dwell-time of objects near apogee, enabling a statistically efficient search for RSOs. During the survey phase, acquired frames are processed in real time using a machine-learning algorithm to enable robust and rapid detection of candidate RSOs. The paper reports on the Molniya population analysis, the results of a campaign comprising 85 observing nights over one year, targeting the eight apogee clusters, and the corresponding detections of both catalogued and uncatalogued objects. Observational arcs of uncatalogued targets acquired on different nights are correlated to refine the orbit reconstruction using standard orbit determination techniques and to enable follow-up. The campaign produced 20,911 astrometric measurements, of which 18,987 could not be correlated with a catalogued object, and yielded 124 uncorrelated tracklets. The results are compared with reference populations derived from multiple catalogues to characterise the observed population and to assess the detection performance of the proposed survey strategy.
Molniya Population Description and Characterization through a Statistical Search Survey Method
Elisa Maria Alessi;Alessandro Rossi;
2026
Abstract
Characterising the space-object population in Highly Elliptical Orbits (HEO) is key to improving our understanding of a region that remains comparatively underexplored. Current debris environment models cover the HEO regime and provide flux and spatial-density estimates. However, this regime remains less described than LEO and GEO, particularly with respect to orbital dynamics characterization, population completeness, and the validation of small-debris distributions at high apogee. As a test case to improve our understanding of the HEO regime, this work presents a Molniya case study. Building on an analysis of the catalogued population, its temporal evolution and the current modelling of this orbital regime, this paper presents a statistical search method for uncatalogued Resident Space Objects (RSOs). The approach couples a dedicated survey strategy with a Stare-and-Chase concept. The population analysis focuses on Molniya-like orbits and defines the orbital selection parameters adopted for the survey. Observations are conducted from the Northern Hemisphere, where the apogees of a significant fraction of Molniya objects cluster because of orbital geometry. At the same time, the currently catalogued population occupies orbits with apogees above the Southern-Hemisphere (at least the 60%). The survey strategy clusters the apogee distribution to identify sky regions with the highest probability of containing uncatalogued objects. Sixteen high-density apogee clusters are derived from the known Molniya population, eight in each hemisphere; the eight Northern-Hemisphere clusters are accessible to the observing site used in this work. The most observable region is then selected, and a mosaic field-of-view grid is designed and optimized by accounting for the expected dwell-time of objects near apogee, enabling a statistically efficient search for RSOs. During the survey phase, acquired frames are processed in real time using a machine-learning algorithm to enable robust and rapid detection of candidate RSOs. The paper reports on the Molniya population analysis, the results of a campaign comprising 85 observing nights over one year, targeting the eight apogee clusters, and the corresponding detections of both catalogued and uncatalogued objects. Observational arcs of uncatalogued targets acquired on different nights are correlated to refine the orbit reconstruction using standard orbit determination techniques and to enable follow-up. The campaign produced 20,911 astrometric measurements, of which 18,987 could not be correlated with a catalogued object, and yielded 124 uncorrelated tracklets. The results are compared with reference populations derived from multiple catalogues to characterise the observed population and to assess the detection performance of the proposed survey strategy.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
