A review of terrain aided navigation for underwater vehicles
Teng Ma, Shuoshuo Ding, Ye Li, Jiajia Fan
Abstract
Underwater terrain aided navigation (TAN) has shown its potential to yield accurate navigational results for long-term operation of underwater vehicles. Due to its independence and remarkable efficiency, TAN has attracted an increasing amount of interest in the field of underwater navigation. A variety of matching algorithms , including terrain correlation, filtering, and graph optimization, may be used to implement a TAN process. These methods make use of terrain data acquired from different sensors and emphasize distinct benefits based on algorithm features. Consequently, numerous previous research attempts have attempted to analyze many TAN technique types using various matching this article, we present a thorough review of recent developments in underwater TAN techniques based on several kinds of matching algorithms. Specifically, we analyze the most popular terrain matching techniques currently in operation, including correlation-based and filter-based techniques, as well as bathymetric simultaneous localization and mapping (BSLAM) techniques based on filtering and graph optimization theories without a priori map. We also address robust extensions of underwater TAN algorithms, along with incisive observations and inspiring future research prospects.