Novel robust skylight compass method based on full-sky polarization imaging under harsh conditions

A novel method based on Pulse Coupled Neural Network(PCNN) algorithm for the highly accurate and robust compass information calculation from the polarized skylight imaging is proposed, which showed good accuracy and reliability especially under cloudy weather, surrounding shielding and moon light. The degree of polarization (DOP) combined with the angle of polarization (AOP), calculated from the full sky polarization image, were used for the compass information caculation. Due to the high sensitivity to the environments, DOP was used to judge the destruction of polarized information using the PCNN algorithm. Only areas with high accuracy of AOP were kept after the DOP PCNN filtering, thereby greatly increasing the compass accuracy and robustness. From the experimental results, it was shown that the compass accuracy was 0.1805 degrees under clear weather. This method was also proven to be applicable under conditions of shielding by clouds, trees and buildings, with a compass accuracy better than 1 degrees. With weak polarization information sources, such as moonlight, this method was shown experimentally to have an accuracy of 0.878 degrees. (C) 2016 Optical Society of America