# Simulation of Dense Star Map in Deep Space Based on Gaia Catalogue

## TL;DR

This paper introduces a high-precision simulation framework for deep-space star fields using the Gaia catalog to improve space situational awareness and target detection.

## Contribution

The novel integration of a full optoelectronic imaging chain with dynamic platform disturbances and realistic noise models using the Gaia catalog.

## Key findings

- The model achieves SNR error of less than 10% when validated against ground-based telescope data.
- Sub-pixel centroiding accuracy exceeds 0.01 pixels, demonstrating high simulation fidelity.
- The framework supports realistic simulation of dim stars at low magnitudes with unprecedented precision.

## Abstract

High-fidelity star field simulation is paramount for target detection and space situational awareness (SSA) in geostationary and deep-space environments. However, accurately modeling the synergistic effects of ultra-dense stellar backgrounds and complex platform perturbations remains a formidable challenge. This paper proposes an integrated simulation framework that leverages the Gaia catalog to generate high-precision stellar environments. The core methodological novelty lies in the end-to-end coupling of a full optoelectronic imaging chain with dynamic platform disturbances, effectively bridging the gap between theoretical orbital dynamics and realistic sensor responses. Distinguishing itself from conventional models, our approach uniquely integrates radiative transfer and high-fidelity noise suites—including photon shot noise and non-uniform stray light—while utilizing the Gaia catalog to achieve unprecedented precision in simulating dim stars at low magnitudes. The fidelity of the proposed model was quantitatively validated against empirical data from a ground-based wide-field telescope (GTC). Experimental results, derived from multiple simulation realizations, demonstrate high consistency with real-world observations, achieving a Signal-to-Noise Ratio (SNR) error of less than 10% and a sub-pixel centroiding accuracy exceeding 0.01 pixels. This work provides a robust, high-fidelity data synthesis tool that significantly advances the development of target detection algorithms and the performance optimization of space-based optical sensors.