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Simultaneous Localization and Mapping (SLAM) is a well-known solution for mapping and realizing autonomous navigation of an Autonomous Underwater Vehicle (AUV) in unknown underwater environments. However, the inaccurate time-varying observation noise will cause filtering divergence and reduce the accuracy of localization and feature estimation. In this paper, VB-AUFastSLAM based on the unscented-FastSLAM (UFastSLAM) and the Variational Bayesian (VB) is proposed. The UFastSLAM combines unscented particle filter (UPF) and unscented Kalman filter (UKF) to estimate the AUV poses and features. In addition, to resist the unknown time-varying observation noise, the method of Variational Bayesian learning is introduced into the SLAM framework. Firstly, the VB method is used to estimate the joint posterior probability of the AUV path and observation noise. The Inverse-Gamma distribution is used to model the observation noise and real-time noise parameters estimation is performed to improve the AUV localization accuracy. Secondly, VB is reused to estimate the noise parameters in the feature update stage to enhance the performance of the feature estimation. The proposed algorithms are first validated in an open-source simulation environment. Then, an AUV SLAM system based on the Inertial Navigation System (INS), Doppler Velocity Log (DVL), and single-beam Sonar are also built to verify the effectiveness of the proposed algorithms in the marine environment. The accuracy of the proposed methods can reach 0.742% and 0.776% of the range, respectively, which is much better than 1.825% and 1.397% of the traditional methods. [ABSTRACT FROM AUTHOR]

In low-earth-orbit (LEO) satellite-to-ground communication, the size of satellite antennae is limited and the satellite motion trajectory is predictable, which makes the channel state information (CSI) of the satellite-to-ground channel easy to leak and impossible to use to generate a physical layer key. To solve these problems, we propose a key generation method based on multi-satellite cooperation and random perturbation. On the one hand, we use multi-satellite cooperation to form a constellation that services users, in order to increase the equivalent aperture of satellite antennae and reduce the correlation between the legal channel and the wiretap channel. On the other hand, according to the endogenous characteristics of satellite motion, a random perturbation factor is proposed, which reflects the randomness of the actual channel and ensures that the CSI of the legal channel is not leaked due to the predictability of satellite motion trajectory. Simulation results show that the proposed method can effectively reduce the leakage of the legal channel's CSI, which makes the method of physical layer key generation safe and feasible in the LEO satellite-to-ground communication scene. [ABSTRACT FROM AUTHOR]