Application of Kalman Filter in AUV Acoustic Navigation

2014 ◽  
Vol 525 ◽  
pp. 695-701 ◽  
Author(s):  
Chang Lin Ji ◽  
Ning Zhang ◽  
Hai Hui Wang ◽  
Cui E Zheng
Keyword(s):  
Autonomous Navigation ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Underwater Acoustic Channel ◽  
Positioning Accuracy ◽  
Position Information ◽  
Long Baseline ◽  
Acoustic Navigation ◽  
Time Information ◽  
Navigation Method

LBL(Long Baseline) positioning provides an important positioning and navigation method for AUV(Autonomous Underwater Vehicle)’s underwater task. Due to the complex underwater acoustic channel, and its poor anti-interference ability, a new feedback Kalman fiter algorithm was present in this paper. By combining travel time information with position information, the state of AUV was estimated accurately. By analyzing experimental results, it showed that the LBL positioning accuracy was improved, and the algorithm ensured AUV complete its autonomous navigation with high precision.

scholarly journals Long-baseline acoustic navigation for under-ice autonomous underwater vehicle operations

2008 ◽  
Vol 25 (11-12) ◽  
pp. 861-879 ◽  
Author(s):  
Michael V. Jakuba ◽  
Christopher N. Roman ◽  
Hanumant Singh ◽  
Christopher Murphy ◽  
Clayton Kunz ◽  
...  
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Long Baseline ◽  
Acoustic Navigation

scholarly journals Underwater terrain-aided navigation method based on improved Gaussian sum particle filtering

2019 ◽  
Vol 16 (1) ◽  
pp. 172988141882157
Author(s):  
Pengyun Chen ◽  
Jianlong Chang ◽  
Yujie Han ◽  
Meini Yuan
Keyword(s):  
Neural Network ◽  
Radial Basis Function ◽  
Particle Filter ◽  
Basis Function ◽  
Particle Filtering ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Gaussian Sum ◽  
Matching Performance ◽  
Navigation Method

To solve the nonlinear Bayesian estimation problem in underwater terrain-aided navigation, a terrain-aided navigation method based on improved Gaussian sum particle filter is proposed. This method approximates the Bayesian function using multiple Gaussian components, and the components can be obtained by radial basis function neural network. This method has no resampling process, the particle depletion of particle filtering is eliminated in principle. The simulation shows that the proposed method has good matching performance, which is suitable for autonomous underwater vehicle navigation.

scholarly journals A Research on the Simultaneous Localization Method in the Process of Autonomous Underwater Vehicle Homing with Unknown Varying Measurement Error

2019 ◽  
Vol 9 (21) ◽  
pp. 4614
Author(s):  
Lingyan Dong ◽  
Hongli Xu ◽  
Xisheng Feng ◽  
Xiaojun Han ◽  
Chuang Yu
Keyword(s):  
Measurement Error ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Gaussian Mixture ◽  
Statistical Characteristics ◽  
Observation System ◽  
Support Vector ◽  
Position Information ◽  
Localization Method ◽  
Working Distance

We propose an acoustic-based framework for automatically homing an Autonomous Underwater Vehicle (AUV) to the fixed docking station (F-DS) and mobile docking station (M-DS). The proposed framework contains a simultaneous localization method of AUV and docking station (DS) and a guidance method based on the position information. The Simultaneous localization and mapping (SLAM) algorithm is not available as the statistical characteristics of the measurement error of the observation system are unknown. To solve this problem, we propose a data pre-processing method. Firstly, the measurement error data of acoustic sensor are collected. Then, We propose a Variational Auto-Encoder (VAE) based Gaussian mixture model (GMM) for estimating the statistical characteristics of measurement error. Finally, we propose a support vector regression (SVR) algorithm to fit the non-linear relationship between the statistical characteristics of measurement error and its corresponding working distance. We adopt a guidance method based on line-of-sight (LOS) and path tracking method for homing an AUV to the fixed docking station (F-DS) and mobile docking station (M-DS). The lake experimental data are used to verify the performance of the localization with the estimated statistical characteristics of measurement error.

scholarly journals An evaluation of path-planning methods for autonomous underwater vehicle based on terrain-aided navigation

2019 ◽  
Vol 16 (3) ◽  
pp. 172988141985318
Author(s):  
Zheng Cong ◽  
Ye Li ◽  
Yanqing Jiang ◽  
Teng Ma ◽  
Yusen Gong ◽  
...  
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Positioning Accuracy ◽  
Planning Methods ◽  
Planning Algorithms ◽  
Motion Characteristics

This article presents a comparison of different path-planning algorithms for autonomous underwater vehicles using terrain-aided navigation. Four different path-planning methods are discussed: the genetic algorithm, the A* algorithm, the rapidly exploring random tree* algorithm, and the ant colony algorithm. The goal of this article is to compare the four methods to determine how to obtain better positioning accuracy when using terrain-aided navigation as a means of navigation. Each algorithm combines terrain complexity to comprehensively consider the motion characteristics of the autonomous underwater vehicles, giving reachable path between the start and end points. Terrain-aided navigation overcomes the challenges of underwater domain, such as visual distortion and radio frequency signal attenuation, which make landmark-based localization infeasible. The path-planning algorithms improve the terrain-aided navigation positioning accuracy by considering terrain complexity. To evaluate the four algorithms, we designed simulation experiments that use real-word seabed bathymetry data. The results of autonomous underwater vehicle navigation by terrain-aided navigation in these four cases are obtained and analyzed.

Research on Signal Aliasing in Long Baseline Positioning System

2014 ◽  
Vol 981 ◽  
pp. 435-439
Author(s):  
Jun Cao ◽  
Da Jun Sun ◽  
Dian Lun Zhang
Keyword(s):  
Signal Detection ◽  
Underwater Vehicle ◽  
Positioning System ◽  
Positioning Accuracy ◽  
Long Baseline ◽  
Simulation Results ◽  
Signal Overlap

In the long baseline positioning system, underwater vehicle use transponder reply signals for positioning and navigation, reply signals aliasing is the main reason of inaccurate detection and instability detection. This paper aimed at the problem and research on signal aliasing in long baseline positioning system, theoretical and simulation results show that: Both overlap degree and overlap energy have a certain distribution. The size of signal aliasing area associated with signal overlap degree. The number of signal aliasing is different in different aliasing area. Signal aliasing will affect signal detection, and reduce the long baseline positioning accuracy.

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