Conceptual Design on the Field of View of Celestial Navigation Systems for Maritime Autonomous Surface Ships

TL;DR

This work tackles GNSS-independent ship positioning by evaluating how the field-of-view (FOV) of celestial-imaging sensors affects star-position measurements and star-identification performance under maritime conditions. It combines a pinhole-camera model to estimate angular resolution, a subgraph-isomorphism-based star-ID framework with an angular-distance database, and Monte Carlo simulations that incorporate ship-environment effects to quantify identification success across FOV sizes. The results show that larger FOV increases observable stars and improves identification probability despite degraded per-star angular accuracy, but observing only four stars (p = 4) may be insufficient for high-FOV cases, requiring matches with more than four stars. The findings provide practical guidance for designing MASS celestial-navigation sensors—favoring the largest feasible FOV that meets the desired positioning accuracy—and highlight calibration and advanced matching techniques needed for wide-angle star pattern matching.

Abstract

In order to understand the appropriate field of view (FOV) size of celestial automatic navigation systems for surface ships, we investigate the variations of measurement accuracy of star position and probability of successful star identification with respect to FOV, focusing on the decreasing number of observable star magnitudes and the presence of physically covered stars in marine environments. The results revealed that, although a larger FOV reduces the measurement accuracy of star positions, it increases the number of observable objects and thus improves the probability of star identification using subgraph isomorphism-based methods. It was also found that, although at least four objects need to be observed for accurate identification, four objects may not be sufficient for wider FOVs. On the other hand, from the point of view of celestial navigation systems, a decrease in the measurement accuracy leads to a decrease in positioning accuracy. Therefore, it was found that maximizing the FOV is required for celestial automatic navigation systems as long as the desired positioning accuracy can be ensured. Furthermore, it was found that algorithms incorporating more than four observed celestial objects are required to achieve highly accurate star identification over a wider FOV.

Figures (12)

• Figure 1: Celestial navigation on board autonomous ships
• Figure 2: Camera coordinate systems
• Figure 3: Cross-sectional view of the hatched area in \ref{['fig:camera']}
• Figure 4: Variation of approximate angular resolution with respect to viewing angle and number of pixels. The right-hand vertical axis shows the distance at sea converted from $\theta_{\mathrm{res}}$.
• Figure 5: Equatorial coordinate systems.