Nikita Sehrawat, Digantara; Shashanka Athigiri, Digantara; Ananthu Krishna, Digantara; Tanveer Ahmed, Digantara; Thamim Ansari, Digantara
Keywords: Space Based SSA, Space Operations, GEO Survey, Optical SBSSA
Abstract:
The growing number of Resident Space Objects (RSOs) poses a significant challenge to space operations across all orbital regimes. Recent breakup events in the geostationary orbit (GEO) region have introduced numerous untracked debris fragments, increasing the risk to operational satellites. Given GEO’s strategic importance in communications, weather monitoring, and defense, enhancing Space Situational Awareness (SSA) in this regime is critical. However, tracking objects in GEO remains challenging due to their low visual magnitude at high altitudes.
Ground-Based SSA (GBSSA) systems, particularly optical sensors, are limited by the diurnal cycle, atmospheric attenuation, and seeing conditions, which hinder their ability to detect GEO objects. In contrast, Space-Based SSA (SBSSA) sensors offer continuous coverage and improved detection capabilities, but their effectiveness depends on optimized operational strategies. These strategies must account for orbital placement, sensor specifications, and mission/payload constraints to maximize detection performance.
This study presents a trade-off analysis of various satellite orbits for GEO surveillance, including Sun-Synchronous Orbits (SSO) with different Local Time of the Ascending Node (LTANs), Low Earth Equatorial (LEO EQ) orbits, and sub-GEO orbits. Additionally, it evaluates different optical systems, considering variations in field of view (FOV) and sensitivity. We propose an optimized GEO survey strategy by extending the traditional staring approach at two illuminated points adjacent to the earth shadow region in GEO belt (GEO2P) to improve coverage. Our approach surveys two vertical fences at GEO to capture high-inclination objects while not missing objects at low-inclinations within the observation window. The strategy is adapted based on different orbit-payload combinations to ensure comprehensive coverage. Key performance metrics—including GEO coverage, revisit rate, and daily observations—are used to evaluate the effectiveness of this method. Additionally, we compare this approach with existing space-based and ground-based survey methods to assess their relative performance in cataloging and maintaining GEO objects.
To support this analysis, we utilize an in-house-developed simulator, the Network Evaluation MOdule (NEMO), integrated with the camera module. The camera module models optical system performance by incorporating critical features such as motion blur, object spot size, point spread function (PSF), atmospheric effects (if applicable), lens transmission, relative illumination, and sensor quantum efficiency (QE). This sophisticated modeling enables the precise simulation of detection filters, allowing legitimate detections to be identified in the presence of background noise.
By integrating these factors, the analysis directly accounts for the optical system’s performance. NEMO facilitates the evaluation of both ground-based and space-based optical SSA sensor networks, providing a validated and comprehensive assessment of various mission configurations.
Preliminary results show that a single SBSSA sensor in a 6 AM SSO at 500 km increases geometrical coverage by 20%, detecting 54.2% of objects with GEO2P and 74.6% with the enhanced GEO survey method. The GEO survey method achieves 19% higher detection coverage compared to the GEO2P method.
In contrast, a single GBSSA sensor achieves only 26.02% geometrical and 25.6% total detection coverage due to geographical constraints and the diurnal cycle.
For this analysis, the SBSSA system has a 4° × 2.5° FOV and a tracking limiting magnitude of 14 with a 0.1-second exposure. A similar GBSSA sensor, operating at a 1-second exposure with a limiting magnitude of 16.8, still offers lower coverage due to restricted observation windows.
These findings highlight the advantages of optimized SBSSA strategies in improving GEO surveillance. By refining operational strategies, this study contributes to advancing SSA capabilities, enhancing the detection, tracking, and monitoring of RSOs in GEO, and supporting long-term space sustainability.
Date of Conference: September 16-19, 2025
Track: Space-Based Assets