Exploration of Whether Skylight Polarization Patterns Contain Three-dimensional Attitude Information
This research addresses a fundamental question for the robotics and navigation community regarding the utility of skylight polarization for 3D attitude estimation, showing that while theoretically possible, practical application is severely limited by noise.
This paper investigates whether skylight polarization patterns contain three-dimensional (3D) attitude information, a question left open by previous work. The authors propose a social spider optimization (SSO) method to estimate three Euler angles using angle of polarization (AOP), degree of polarization (DOP), and light intensity (LI) information. Simulation results indicate that the SSO algorithm can estimate 3D attitude and the sky model contains this information, but accuracy significantly degrades with measurement noise or model error, making field estimation very difficult.
Our previous work has demonstrated that Rayleigh model, which is widely used in polarized skylight navigation to describe skylight polarization patterns, does not contain three-dimensional (3D) attitude information [1]. However, it is still necessary to further explore whether the skylight polarization patterns contain 3D attitude information. So, in this paper, a social spider optimization (SSO) method is proposed to estimate three Euler angles, which considers the difference of each pixel among polarization images based on template matching (TM) to make full use of the captured polarization information. In addition, to explore this problem, we not only use angle of polarization (AOP) and degree of polarization (DOP) information, but also the light intensity (LI) information. So, a sky model is established, which combines Berry model and Hosek model to fully describe AOP, DOP, and LI information in the sky, and considers the influence of four neutral points, ground albedo, atmospheric turbidity, and wavelength. The results of simulation show that the SSO algorithm can estimate 3D attitude and the established sky model contains 3D attitude information. However, when there are measurement noise or model error, the accuracy of 3D attitude estimation drops significantly. Especially in field experiment, it is very difficult to estimate 3D attitude. Finally, the results are discussed in detail.