Study on the observability degree of integrated inertial navigation system of autonomous underwater vehicle

2020 ◽  
Vol 12 (3) ◽  
pp. 359
Author(s):  
Qi Wang ◽  
Chang song Yang ◽  
Yu xiang Wang
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Autonomous Underwater Vehicle ◽  
Inertial Navigation ◽  
Underwater Vehicle

scholarly journals Correction Algorithm for the Navigation System of an Autonomous Unmanned Underwater Vehicle

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2365
Author(s):  
Danhe Chen ◽  
K. A. Neusypin ◽  
M. S. Selezneva
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Underwater Vehicle ◽  
Measurement Information ◽  
Nonlinear Controller ◽  
Unmanned Underwater Vehicle ◽  
Measuring Complex ◽  
Nonlinear Kalman Filter

More accurate navigation systems are always required for autonomous unmanned underwater vehicles (AUUV)s under various circumstances. In this paper, a measuring complex of a heavy unmanned underwater vehicle (UUV) was investigated. The measuring complex consists of an inertial navigation platform system, a Doppler lag (DL) and an estimation algorithm. During a relatively long-term voyage of an UUV without surfacing and correction from buoys and stationary stations, errors of the measuring complex will increase over time. The increase in errors is caused by an increase in the deviation angles of the gyro platform relative to the accompanying trihedron of the selected coordinate system. To reduce these angles, correction is used in the structure of the inertial navigation system (INS) using a linear regulator. To increase accuracy, it is proposed to take into account the nonlinear features of INS errors; an adaptive nonlinear Kalman filter and a nonlinear controller were used in the correction scheme. Considering that, a modified nonlinear Kalman filter and a regulator in the measuring complex are proposed to improve the accuracy of the measurement information, and modification of the nonlinear Kalman filter was performed through a genetic algorithm, in which the regulator was developed by the State Dependent Coefficient (SDC) method of the formulated model. Modeling combined with a semi-natural experiment with a real inertial navigation system for the UUV demonstrated the efficiency and effectiveness of the proposed algorithms.

A Study on Fault Detection Method of Redundant Inertial Navigation System on Micro AUV

2014 ◽  
Vol 709 ◽  
pp. 473-479 ◽  
Author(s):  
Kun Peng He ◽  
Yu Ping Shao ◽  
Lin Zhang ◽  
Shou Lei Hu ◽  
Yuan Li
Keyword(s):  
Fault Detection ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Autonomous Underwater Vehicle ◽  
Inertial Navigation ◽  
Optimization Method ◽  
Fault Detection And Isolation ◽  
Measurement Unit ◽  
Support Vector ◽  
Ratio Test

In order to improve the precision and reliability of the autonomous underwater vehicle (AUV) inertial navigation system, a redundant inertial measurement unit (RIMU) based on micro electromechanical system (MEMS) inertial sensors has been designed, then use support vector machine theory (SVM),construct multi-fault classifier training and combine three-step search parameter optimization method,to achieve rapid, automatic fault detection and isolation (FDI). With Monte Carlo simulation and experimental analysis, SVM method has more obvious advantages than conventional Generalized Likelihood ratio Test (GLT) on false alarm rate, undetected rate and correct isolation rate for common fault sources of RIMU, and can detect and identify the type and number of failure more effectively on redundant systems, and provide a guarantee for fault sensors isolation.

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