Abstract
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.
Highlights
The Arctic region is rich in underwater minerals, diverse organisms, and shipping resources with great development potential
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
We study the navigation ability of Autonomous Underwater Vehicles (AUVs) under the ultralow-resolution terrain map
Summary
The Arctic region is rich in underwater minerals, diverse organisms, and shipping resources with great development potential. Terrain-aided navigation only uses the range sensor to obtain the altitude data, which can achieve a better localization accuracy. It has been widely used in aircraft [7, 8], space landers, and underwater vehicles [9] because it does not need the aid of external sensors. In [21], fuzzy logic is used to dynamically adjust the process noise and particle numbers, effectively filters out the disturbance in different environments, and improves the accuracy of target recognition. The dynamic adjustment method of process noise of particle filter based on fuzzy logic is proposed
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