Global Autonomous Positioning Based on Celestial Polarized Light and Starlight Fusion

It is extremely important for autonomous systems positioning in global navigation satellite system (GNSS) challenged night environment. Nevertheless, nocturnal animals with remarkable visual capability have sufficient visual cues for navigation. Inspired by animals' navigation scheme, an integrated positioning strategy of combining the moonlit polarization patterns and celestial starlight is presented, which can enhance the autonomous navigation ability of unmanned systems in the GNSS denied environment at night. First, the geometric relationship between geographical position and observed polarization-star angle is modeled. Subsequently, the positioning task can be modeled as a nonlinear optimization problem without priori knowledge of the altitude and azimuth of the celestial body. Further, based on matrix theory, a simplified solution method is derived for solving the observer's position. Finally, the simulations are conducted to validate the effectiveness of the proposed scheme.