  This paper proposes an artificial neural network to determine orientation
using polarized skylight. This neural network has specific dilated convolution,
which can extract light intensity information of different polarization
directions. Then, the degree of polarization (DOP) and angle of polarization
(AOP) are directly extracted in the network. In addition, the exponential
function encoding of orientation is designed as the network output, which can
better reflect the insect's encoding of polarization information, and improve
the accuracy of orientation determination. Finally, training and testing were
conducted on a public polarized skylight navigation dataset, and the
experimental results proved the stability and effectiveness of the network.
