Uncertainty Analysis of Ultra-Short- and Long- Baseline Localization Systems for Autonomous Underwater Vehicles

2018 ◽  
Author(s):  
David Pick ◽  
Eric Wolbrecht ◽  
Michael Anderson ◽  
Dean Edwards ◽  
John Canning
Keyword(s):  
Uncertainty Analysis ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Long Baseline ◽  
Localization Systems

scholarly journals Application of a Real-Time Visualization Method of AUVs in Underwater Visual Localization

2019 ◽  
Vol 9 (7) ◽  
pp. 1428 ◽  
Author(s):  
Ran Wang ◽  
Xin Wang ◽  
MingMing Zhu ◽  
YinFu Lin
Keyword(s):  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Visual Localization ◽  
Visualization Method ◽  
Localization And Mapping ◽  
Real Time Visualization ◽  
Novel Method ◽  
Vision Based Localization ◽  
Slam Algorithm ◽  
Localization Systems

Autonomous underwater vehicles (AUVs) are widely used, but it is a tough challenge to guarantee the underwater location accuracy of AUVs. In this paper, a novel method is proposed to improve the accuracy of vision-based localization systems in feature-poor underwater environments. The traditional stereo visual simultaneous localization and mapping (SLAM) algorithm, which relies on the detection of tracking features, is used to estimate the position of the camera and establish a map of the environment. However, it is hard to find enough reliable point features in underwater environments and thus the performance of the algorithm is reduced. A stereo point and line SLAM (PL-SLAM) algorithm for localization, which utilizes point and line information simultaneously, was investigated in this study to resolve the problem. Experiments with an AR-marker (Augmented Reality-marker) were carried out to validate the accuracy and effect of the investigated algorithm.

scholarly journals A Single-Way Ranging Localization of AUVs Based on PSO of Outliers Elimination

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Xinnan Fan ◽  
Zhongjian Wu ◽  
Jianjun Ni ◽  
Chengming Luo
Keyword(s):  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Time Of Arrival ◽  
Localization Algorithm ◽  
Angle Of Arrival ◽  
Simulation Experiments ◽  
Range Measurements ◽  
Acoustic Localization ◽  
Long Baseline ◽  
Key Factor

Localization of autonomous underwater vehicles (AUVs) is a very important and challenging task for the AUVs applications. In long baseline underwater acoustic localization networks, the accuracy of single-way range measurements is the key factor for the precision of localization of AUVs, whether it is based on the way of time of arrival (TOA), time difference of arrival (TDOA), or angle of arrival (AOA). The single-way range measurements do not depend on water quality and can be taken from long distances; however, there are some limitations which exist in these measurements, such as the disturbance of the unknown current velocity and the outliers caused by sensors and errors of algorithm. To deal with these problems, an AUV self-localization algorithm based on particle swarm optimization (PSO) of outliers elimination is proposed, which improves the performance of angle of arrival (AOA) localization algorithm by taking account of effects of the current on the positioning accuracy and eliminating possible outliers during the localization process. Some simulation experiments are carried out to illustrate the performance of the proposed method compared with another localization algorithm.

Observability Analysis for MAUVs Cooperative Navigation System Based on Moving Long Baseline

2013 ◽  
Vol 475-476 ◽  
pp. 609-615
Author(s):  
Peng Ma ◽  
Fu Bin Zhang ◽  
De Min Xu ◽  
Shao Kun Yang
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Simulation Experiments ◽  
Cooperative Navigation ◽  
Long Baseline ◽  
Simulation Results ◽  
Moving Long Baseline ◽  
Theoretical Results

This paper addresses the observability problem of 2D Multiple Autonomous Underwater Vehicles (MAUVs) cooperative navigation system. We derive the conditions to keep the local weak observability of navigation system using the Lie derivatives, and characterize the unobservable trajectories of AUVs. We design a series of simulation experiments using the Extended Kalman Filter (EKF) to verify the theoretical results. Finally, the simulation results show that the good performance of navigation system can be presented if avoiding the unobservable trajectories of AUVs.

scholarly journals Test Results of the Long Baseline Navigation Solutions under a Large a Priori Position Uncertainty

2022 ◽  
Vol 1215 (1) ◽  
pp. 012006
Author(s):  
V.V. Bogomolov
Keyword(s):  
Autonomous Underwater Vehicles ◽  
A Priori ◽  
Underwater Vehicles ◽  
Posteriori Probability ◽  
Global Maximum ◽  
Test Results ◽  
Final Solution ◽  
Position Uncertainty ◽  
Modified Method ◽  
Long Baseline

Abstract A method is proposed for long baseline navigation of autonomous underwater vehicles (AUV) to be used in the case of a large a priori position uncertainty. The new modified method is based on the iterated Kalman filter (IKF) working with different initial linearization points. The final solution is calculated by clustering and weighting the IKF results. This approach allows position estimates to be determined in accordance with the global maximum of posteriori probability density of coordinates. The test results obtained with the use of three beacons and an underwater vehicle are presented.

Cooperative Navigation for Multiple AUVs Based on Relative Range Measurements with a Single Leader

2014 ◽  
Vol 556-562 ◽  
pp. 3117-3123 ◽  
Author(s):  
Xing Li Huang ◽  
Li Yan Liu ◽  
Tao Tao Lv ◽  
Wen Bai Li
Keyword(s):  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Cooperative Localization ◽  
Positioning System ◽  
Navigation Problem ◽  
Range Measurements ◽  
Cooperative Navigation ◽  
Long Baseline ◽  
Novel Method ◽  
Simulation Results

his paper deals with the cooperative navigation problem of multiple autonomous underwater vehicles (AUV). A novel method which does not depend on a beacon network like in long baseline positioning system is proposed. The principle of this approach is to realize the cooperative localization of AUVs by using relative range measurements between the leader and the follower vehicles by means of an extended Kalman filter. Simulation results that validate the effectiveness of this approach are presented.

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