Autonomous nighttime navigation with lunar polarized light: A 3-D attitude determination approach

Nighttime navigation faces challenges from limited data and interference, especially when satellite signals are unavailable. Leveraging lunar polarized light, polarization navigation offers a promising solution for nighttime autonomous navigation. Current algorithms, however, are limited by the requirement for known horizontal attitudes, restricting applications. This study introduces an autonomous 3-D attitude determination method to overcome this limitation. Our approach utilizes the Angle of Polarization (AOP) at night to extract neutral points from the AOP pattern. This allows for the calculation of polarization meridian plane information for attitude determination. Subsequently, we present an optimized Polarization TRIAD (Pol-TRIAD) algorithm to acquire the 3-D attitude. The proposed method outperforms the existing approaches in outdoor experiments by achieving lower Root Mean Square Error (RMSE). For one baseline attitude, it improves pitch by 31.7%, roll by 21.7%, and yaw by 2.6%, while for the attitude with a larger tilt angle, the improvements are 64.4%, 30.4%, and 9.1%, respectively.