Optimal Triangulation Based Optical Celestial Navigation for Deep-Space Missions

Date

2026-1-20

Author

Muratoğlu, Abdurrahim

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Autonomous navigation for deep-space missions has become increasingly critical as spacecraft venture further into the solar system, where communication delays render real-time ground-based control impractical. Triangulation-based vision-aided navigation systems employing line-of-sight measurements to celestial bodies offer promising solutions for onboard position estimation. Existing approaches face particular challenges: triangulation accuracy, and thus position estimation reliability, varies dramatically with the geometric configuration between the spacecraft and observed bodies throughout the trajectory; the trade-off between beacon utilization and computational efficiency remains poorly characterized. This research addresses these limitations through a framework based on the Cramér-Rao Lower Bound (CRLB). A geometric performance metric is developed to quantify the theoretical minimum achievable estimation error variance for any observation count and configuration, enabling systematic evaluation of triangulation quality. Within the Linear Optimal Sine Triangulation (LOST) framework, the proposed Improved-LOST algorithm employs this metric to optimize beacon pairs, demonstrating substantial accuracy improvements, particularly during geometrically challenging trajectory segments. An adaptive measurement covariance adjustment methodology is introduced for Kalman Filters, utilizing the CRLB-based metric to characterize measurement reliability under dynamic geometric conditions. Additionally, a threshold-based beacon selection methodology is established to systematically determine a sufficient number of beacons, demonstrating that carefully selected subsets can approach maximum theoretical accuracy while avoiding substantial computational burden. Computational efficiency analyses reveal that optimal beacon configurations are most effectively determined during mission planning rather than through real-time onboard processing. The developed frameworks provide mission designers with systematic tools for enhancing autonomous navigation performance in resource-constrained deep-space environments, enabling informed decisions regarding sensor utilization, filter tuning, and trajectory design accounting for geometric observability.

Subject Keywords

Optical Navigation, Deep-Space Navigation, Optimal Triangulation, Beacon Optimization, Cramér–Rao Lower Bound

URI

https://hdl.handle.net/11511/118468

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Graduate School of Natural and Applied Sciences, Thesis