Environmental adaptive enhancement for the bionic polarized compass based on multi-scattering light model

The bio-polarized compass is an autonomous navigation technology with long-term endurance that has recently attracted the attention of numerous researchers. However, current algorithms for polarimetric compasses based on a single scattering model demonstrate poor adaptability to environmental perturbations. Numerous academic studies have conclusively demonstrated that the multi-scattering model provides a more accurate approximation of the actual scenario. Inspired by insects, we find that multi-scattering models have better environmental adaptability. However, the mathematical formalism of multi-scattering models is generally complex, making it difficult to obtain the solar vector directly from the polarization pattern. Therefore, we propose an inverse algorithm that combines the simulated annealing algorithm and a multi-scattering model, the equivalent incident light model(EIL model), to derive the solar vector from the polarized pattern with strong environmental adaptability. Five experimental sets were conducted across diverse environments, revealing that the errors associated with the bionic polarized compass are consistently below 0.4°, representing a substantial improvement compared to existing compass technology.