The TU Delft Astrodynamics Toolbox (Tudat) is a free open-source software (FOSS) suite geared towards research and education in computational astrodynamics. It has been applied primarily to numerical simulation of the dynamics of objects in space, ranging from optimization of re-entry vehicle dynamics to the modeling of planetary spacecraft tracking and the dynamics of natural solar system bodies. The powerful and versatile estimation module of Tudat has been used for a broad range of studies for both current and future space missions. It has the capability to combine optical and radiometric tracking data from multiple spacecraft with Earth-based observations into a comprehensive estimation of the dynamics of both natural and artificial solar system bodies, as well as physical parameters of interest. Building upon this general and adaptable framework, recent developments have focused on incorporating the necessary functionality required for real tracking data analysis. In this paper, we present the integration of these capabilities into Tudat’s fully open-source framework, with a combined focus on planetary missions and Space Situational Awareness (SSA). At present, the software provides capabilities to process several categories of observational data: (i) deep-space Doppler and range tracking data of planetary missions collected by the Deep Space Network (DSN) and ESA’s ESTRACK, supporting multiple formats such as IFMS, ODF, and TNF; (ii) deep-space Doppler and VLBI tracking data of planetary missions collected by the Planetary and Radio Interferometry and Doppler Experiment (PRIDE) with radio (astronomy) telescopes; (iii) optical astrometry and radar tracking archived by the Minor Planet Center (MPC) and the Natural Satellite Data Center (NSDC). By computing observation residuals using existing orbital solutions as references, we show that our observation models are accurate to the intrinsic quality of the data (e.g., better than 0.05 mm/s for typical deep-space Doppler data). Additionally, we demonstrate that our dynamical models possess the level of fidelity necessary to enable precise orbit estimation, effectively leveraging the high quality of the available tracking data. Tudat is unique in providing modular and flexible open-source high-fidelity modeling across a broad range of orbital regimes, enabling interdisciplinary applications. We provide an overview of the data processing and estimation capabilities and give examples from various mission domains. These include high-precision orbit estimation using deep-space Doppler tracking data, orbit determination of cis-lunar/xGEO space debris in highly non-linear regimes (specifically targeting upper stages of lunar missions) from astrometric data, and estimation of small solar system bodies using astrometric data.

We introduce a refined formulation of the Fragmentation Environmental Index (FEI), designed to assess changes in the Low Earth Orbit (LEO) environment resulting from the fragmentation of a specific mass. The index quantifies this impact by comparing overall LEO criticalities before and after the fragmentation event. To highlight the contribution of smaller debris, we enhance the index by incorporating weighting factors tailored to optical and radar surveillance networks. Testing of the upgraded FEI on a series of simulated fragmentation events shows that it can characterize both the perturbation to the LEO environment and its temporal evolution, providing a more accurate quantification of the short- and medium-term impact of debris clouds compared to the original formulation.

Building on the definition of the Criticality of Spacecraft Index [1] and of the Shell Criticality [3], a procedure and an index able to quantify and visualize the medium term effects on the environment of a fragmentation in Low Earth Orbit is derived. The index takes into account the change in the environment caused by the fragmentation of a given mass in a specific orbit by quantifying the contribution of the fragments with respect to the original situation where the whole fragmented mass was contained in the intact objects. The index is devised in the frame of added-value SST services, such as the fragmentation detection and impact evaluation service. Thus, weighting factors are included in its formulation to highlight the contribution of the debris created in a given event, leveraged by the capabilities of a given observing network (either optical or radar). The index is applied and tested on a few simulated fragmentations. The results show that the index is able to characterize the perturbation to the environment due to the cloud of fragments and its temporal evolution. In particular, the new weighting factors are able to properly highlight the capability of a given SST network to observe and characterize a fragmentation happening in a Low Earth Orbit region.