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Polar Grid Navigation Algorithm for Unmanned Underwater Vehicles.

作者信息

Yan Zheping, Wang Lu, Zhang Wei, Zhou Jiajia, Wang Man

机构信息

Marine Assembly and Automatic Technology Institute, College of Automation, Harbin Engineering University; Harbin 150001, China.

出版信息

Sensors (Basel). 2017 Jul 9;17(7):1599. doi: 10.3390/s17071599.


DOI:10.3390/s17071599
PMID:28698498
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5539858/
Abstract

To solve the unavailability of a traditional strapdown inertial navigation system (SINS) for unmanned underwater vehicles (UUVs) in the polar region, a polar grid navigation algorithm for UUVs is proposed in this paper. Precise navigation is the basis for UUVs to complete missions. The rapid convergence of Earth meridians and the serious polar environment make it difficult to establish the true heading of the UUV at a particular instant. Traditional SINS and traditional representation of position are not suitable in the polar region. Due to the restrictions of the complex underwater conditions in the polar region, a SINS based on the grid frame with the assistance of the OCTANS and the Doppler velocity log (DVL) is chosen for a UUV navigating in the polar region. Data fusion of the integrated navigation system is realized by a modified fuzzy adaptive Kalman filter (MFAKF). By neglecting the negative terms, and using T-S fuzzy logic in the adaptive regulation of the noise covariance, the proposed filter algorithm can improve navigation accuracy. Simulation and experimental results demonstrate that the polar grid navigation algorithm can effectively navigate a UUV sailing in the polar region.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/5539858/ba959b873dcf/sensors-17-01599-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/5539858/dd74be46fc48/sensors-17-01599-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/5539858/2b277a832067/sensors-17-01599-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/5539858/ea96aff04ad9/sensors-17-01599-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/5539858/62686cf3fc6a/sensors-17-01599-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/5539858/aa89bc635c6c/sensors-17-01599-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/5539858/d66d1364a2be/sensors-17-01599-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/5539858/746ccde9afe4/sensors-17-01599-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/5539858/72e97de38352/sensors-17-01599-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/5539858/ba959b873dcf/sensors-17-01599-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/5539858/dd74be46fc48/sensors-17-01599-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/5539858/2b277a832067/sensors-17-01599-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/5539858/ea96aff04ad9/sensors-17-01599-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/5539858/62686cf3fc6a/sensors-17-01599-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/5539858/aa89bc635c6c/sensors-17-01599-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/5539858/d66d1364a2be/sensors-17-01599-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/5539858/746ccde9afe4/sensors-17-01599-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/5539858/72e97de38352/sensors-17-01599-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/5539858/ba959b873dcf/sensors-17-01599-g009.jpg

相似文献

[1]
Polar Grid Navigation Algorithm for Unmanned Underwater Vehicles.

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[2]
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[3]
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[4]
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[5]
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[6]
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[7]
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[8]
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[9]
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[10]
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引用本文的文献

[1]
A Vision Aided Initial Alignment Method of Strapdown Inertial Navigation Systems in Polar Regions.

Sensors (Basel). 2022-6-21

[2]
Mini-AUV Hydrodynamic Parameters Identification via CFD Simulations and Their Application on Control Performance Evaluation.

Sensors (Basel). 2021-1-26

[3]
Attitude Estimation of Underwater Vehicles Using Field Measurements and Bias Compensation.

Sensors (Basel). 2019-1-15

[4]
Economical High⁻Low Temperature and Heading Rotation Test Method for the Evaluation and Optimization of the Temperature Control System for High-Precision Platform Inertial Navigation Systems.

Sensors (Basel). 2018-11-15

[5]
Hybrid Transverse Polar Navigation for High-Precision and Long-Term INSs.

Sensors (Basel). 2018-5-12

[6]
Polar Cooperative Navigation Algorithm for Multi-Unmanned Underwater Vehicles Considering Communication Delays.

Sensors (Basel). 2018-3-30

[7]
Leader-Follower Formation Control of UUVs with Model Uncertainties, Current Disturbances, and Unstable Communication.

Sensors (Basel). 2018-2-23

[8]
Dynamic Obstacle Avoidance for Unmanned Underwater Vehicles Based on an Improved Velocity Obstacle Method.

Sensors (Basel). 2017-11-27

[9]
A Polar Initial Alignment Algorithm for Unmanned Underwater Vehicles.

Sensors (Basel). 2017-11-23

[10]
A New Polar Transfer Alignment Algorithm with the Aid of a Star Sensor and Based on an Adaptive Unscented Kalman Filter.

Sensors (Basel). 2017-10-23

本文引用的文献

[1]
An Improved Alignment Method for the Strapdown Inertial Navigation System (SINS).

Sensors (Basel). 2016-4-29

[2]
A novel scheme for DVL-aided SINS in-motion alignment using UKF techniques.

Sensors (Basel). 2013-1-15

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