NEOPROP: a NEO Propagator for Space Situational Awareness

TL;DR

NEOPROP is a new software tool designed to improve the prediction and impact risk assessment of Near-Earth Objects by combining analytical and numerical algorithms for space situational awareness.

Contribution

It introduces a novel trajectory prediction algorithm for NEOs that allows independent validation of existing systems within the SSA framework.

Findings

Developed the NEOPROP software with analytical and numerical modules.

Validated the trajectory prediction algorithm against existing systems.

Enhanced impact risk assessment capabilities for NEOs.

Abstract

The overall aim of the Space Situational Awareness (SSA) Preparatory Programme is to support the European independent utilisation of and access to space for research or services, through providing timely and quality data, information, services and knowledge regarding the environment, the threats and the sustainable exploitation of the outer space surrounding our planet Earth. The SSA system will comprise three main segments: Space Weather (SWE) monitoring and forecast Near-Earth Objects (NEO) survey and follow-up Space Surveillance and Tracking (SST) of man-made space objects. There already exist different algorithms to predict orbits for NEOs. The objective of this activity is to come up with a different trajectory prediction algorithm, which allows an independent validation of the current algorithms within the SSA-NEO segment (e.g. NEODyS, JPL Sentry System). The key objective of this activity was to design, develop, test, verify, and validate trajectory prediction algorithm of NEOs in order to be able to compute analytically and numerically the minimum orbital intersection distances (MOIDs). The NEOPROP software consists of two separate modules/tools: (i) the Analytical Module makes use of analytical algorithms in order to rapidly assess the impact risk of a NEO. (ii) The Numerical Module makes use of numerical algorithms in order to refine and to better assess the impact probabilities.