  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.
