In this paper, a new outlier-robust Student's t based Gaussian approximate filter is proposed to address the heavytailed process and measurement noises induced by the outlier measurements of velocity and range in cooperative localization of autonomous underwater vehicles (AUVs). The state vector, scale matrices and degrees of freedom (dof) parameters are estimated based on the variational Bayesian approach by using the constructed Student's t based hierarchical Gaussian statespace model. The performances of the proposed filter and existing filters are tested in the cooperative localization of an AUV through a lake trial. Experimental results illustrate that the proposed filter has better localization accuracy and robustness than existing state-of-the-art outlier-robust filters.

Both theoretically and experimentally, we demonstrate that the photonic band gaps in Thue–Morse aperiodic systems can be separated into two flavors, the fractal gaps and the traditional gaps, distinguished by the presence or absence of fractal structure, respectively. The origin of two kind gaps is explained by the different interface correlations. This explanation is confirmed by the gap width behaviors. In addition, the eigenstates near the fractal gaps have a cluster-periodic form, while those near the traditional gaps have the Bloch wavelike form. Our detailed study of these differences is essential for understanding the spectra and light localization in aperiodic systems.

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