The ultra-low resolution underwater terrain maps of the Arctic region reduce the localization and navigation accuracy of the underwater vehicle relying on terrain-aided navigation. In this paper, we study the navigation ability of Autonomous Underwater Vehicles (AUVs) under the ultralow-resolution terrain map. Firstly, the low-resolution map is transformed into a continuous map by bilinear interpolation. Then, a Terrain-Aided Navigation (TAN) system based on the Particle Filter (PF) is constructed to estimate the state of AUV position by particles. Particles of a random distribution of fixed variance can effectively track targets. However, a fixed variance distribution is not well adapted to many different situations. To improve navigation accuracy and robustness, fuzzy logic is used to estimate the distribution variance of particles under the current terrain gradient dynamically. The simulation results show that our proposed Fuzzy-PF TAN system is robust under various current disturbance situations. The position error of our system is within a map resolution unit of 500 m.

北极地区的超低分辨率水下地形图降低了依靠地形辅助导航的水下航行器的定位和导航精度。在本文中，我们研究了超低分辨率地形图下的自动水下航行器（AUV）的导航能力。首先，通过双线性插值将低分辨率图转换为连续图。然后，构建了基于粒子过滤器（PF）的地形辅助导航（TAN）系统，以估计粒子的AUV位置状态。固定方差的随机分布的粒子可以有效地跟踪目标。但是，固定的方差分布不能很好地适应许多不同的情况。为了提高导航的准确性和鲁棒性，模糊逻辑用于动态估计当前地形梯度下的粒子分布方差。仿真结果表明，我们提出的Fuzzy-PF TAN系统在各种电流干扰情况下均具有鲁棒性。我们系统的位置误差在500 m的地图分辨率范围内。