scholarly journals An acoustic-based approach for real-time deep-water navigation of an AUV

2018 ◽  
Author(s):  
A Tesei ◽  
M Micheli ◽  
A Vermeij ◽  
G Ferri ◽  
M Mazzi ◽  
...  
Keyword(s):  
Real Time ◽  
Deep Water ◽  
Autonomous Underwater Vehicles ◽  
Accurate Estimate ◽  
Doppler Velocity ◽  
Positioning System ◽  
Navigation Systems ◽  
June July ◽  
Proprioceptive Sensors ◽  
Acoustic Positioning

Navigation of Autonomous Underwater Vehicles (AUVs) remains a challenge due to the impossibility to use radio frequency signals and Global Positioning System (GPS). Navigation systems usually integrate different proprioceptive sensors to estimate the asset and the speed of the vehicle. In particular, the Doppler Velocity Log (DVL) is fundamental during the navigation to have an accurate estimate of the vehicle’s speed. This work addresses the enhancement of the navigation performance of an AUV through the development of a Deep Water Navigation Filter (DWNF). The DWNF is able to work in those scenarios where traditional navigation sensors show their limits: e.g., deep waters where DVL bottom lock cannot be achieved, or areas where the use of traditionally used static and dedicated beacons is incompatible with the mission requirements. The proposed approach exploits the concept of using a network of vehicles cooperatively supporting each other for their navigation. Several types of measurements coming from the different nodes (i.e. acoustic positioning system such as ship-mounted SSBL acoustic positioning system, USBL, range measurements from the different nodes) are fused in an Extended Kalman Filter framework with the odometry data. DWNF pushes forward the idea of using a network of robotic assets as a provider of navigation services allowing more flexible and robust operations of the deployed system. The approach has been tested at sea during several experiments. We report here results from DWNF running successfully in real-time on the NATO STO-Centre for Maritime Research and Experimentation (CMRE) vehicles during the Dynamic Mongoose’17 experimentation off the South coast of Iceland (June-July 2017). 

Low-Altitude and High-Speed Terrain Tracking Method for Lightweight AUVs

2018 ◽  
Vol 30 (6) ◽  
pp. 971-979 ◽  
Author(s):  
Toshihiro Maki ◽  
Yukiyasu Noguchi ◽  
Yoshinori Kuranaga ◽  
Kotohiro Masuda ◽  
Takashi Sakamaki ◽  
...  
Keyword(s):  
High Speed ◽  
Low Cost ◽  
Autonomous Underwater Vehicles ◽  
Vertical Plane ◽  
Potential Method ◽  
Visual Observation ◽  
Doppler Velocity ◽  
Navigation Systems ◽  
Inertial Navigation Systems ◽  
Constant Altitude

This paper proposes a new method for cruising-type autonomous underwater vehicles (AUVs) to track rough seafloors at low altitudes while also maintaining a high surge velocity. Low altitudes are required for visual observation of the seafloor. The operation of AUVs at low altitudes and high surge velocities permits rapid seafloor imaging over a wide area. This method works without high-grade sensors, such as inertial navigation systems (INS), Doppler velocity logs (DVL), or multi-beam sonars, and it can be implemented in lightweight AUVs. The seafloor position is estimated based on a reflection intensity map defined on a vertical plane, using measurements from scanning sonar and basic sensors of depth, attitude, and surge velocity. Then, based on the potential method, a reference pitch angle is generated that allows the AUV to follow the seafloor at a constant altitude. This method was implemented in the AUV HATTORI, and a series of sea experiments were carried out to evaluate its performance. HATTORI (Highly Agile Terrain Tracker for Ocean Research and Investigation) is a lightweight and low-cost testbed designed for rapid and efficient imaging of rugged seafloors, such as those containing coral reefs. The vehicle succeeded in following a rocky terrain at an altitude of approximately 2 m with a surge velocity of approximately 0.8 m/s. This paper also presents the results of sea trials conducted at Ishigaki Island in 2017, where the vehicle succeeded in surveying the irregular, coral-covered seafloor.

GPS RTK Techniques for Construction Monitoring of Super Deep-Water Open-Caisson

2014 ◽  
Vol 580-583 ◽  
pp. 2865-2871
Author(s):  
Yan Guang Hao ◽  
Xiang Liang Liu ◽  
Jian Bo Liu
Keyword(s):  
Real Time ◽  
Deep Water ◽  
Yangtze River ◽  
Positioning System ◽  
Construction Monitoring ◽  
Construction Period ◽  
Gps Rtk

The super open-caisson foundation of Taizhou Yangtze River Bridge was used by positioning system of anchor piers. GPS RTK Techniques was used to real-time monitor the open-caisson and by software compute current geometric posture of open-caisson timely. This could provide guarantee for sinking of caisson, and shorten construction period and save cost.

scholarly journals A SINS/DVL Integrated Positioning System through Filtering Gain Compensation Adaptive Filtering

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4576
Author(s):  
Xiaozhen Yan ◽  
Yipeng Yang ◽  
Qinghua Luo ◽  
Yunsai Chen ◽  
Cong Hu
Keyword(s):  
Adaptive Filtering ◽  
Autonomous Underwater Vehicles ◽  
Doppler Velocity ◽  
Positioning System ◽  
Positioning Error ◽  
Error Statistics ◽  
Positioning Accuracy ◽  
Position Information ◽  
Filtering Method ◽  
Gain Compensation

Because of the complex task environment, long working distance, and random drift of the gyro, the positioning error gradually diverges with time in the design of a strapdown inertial navigation system (SINS)/Doppler velocity log (DVL) integrated positioning system. The use of velocity information in the DVL system cannot completely suppress the divergence of the SINS navigation error, which will result in low positioning accuracy and instability. To address this problem, this paper proposes a SINS/DVL integrated positioning system based on a filtering gain compensation adaptive filtering technology that considers the source of error in SINS and the mechanism that influences the positioning results. In the integrated positioning system, an organic combination of a filtering gain compensation adaptive filter and a filtering gain compensation strong tracking filter is explored to fuse position information to obtain higher accuracy and a more stable positioning result. Firstly, the system selects the indirect filtering method and uses the integrated positioning error to model the navigation parameters of the system. Then, a filtering gain compensation adaptive filtering method is developed by using the filtering gain compensation algorithm based on the error statistics of the positioning parameters. The positioning parameters of the system are filtered and information on errors in the navigation parameters is obtained. Finally, integrated with the positioning parameter error information, the positioning parameters of the system are solved, and high-precision positioning results are obtained to accurately position autonomous underwater vehicles (AUVs). The simulation results show that the SINS/DVL integrated positioning method, based on the filtering gain compensation adaptive filtering technology, can effectively enhance the positioning accuracy.

Thruster Design for Acoustic Positioning Systems

1975 ◽  
Vol 12 (02) ◽  
pp. 122-137
Author(s):  
Neal A. Brown ◽  
John A. Norton
Keyword(s):  
Positioning System ◽  
Navigation Systems ◽  
Noise Levels ◽  
Cavitation Noise ◽  
Positioning Systems ◽  
Ocean Drilling ◽  
Cavitation Performance ◽  
Propeller Blades ◽  
Large Improvement ◽  
Acoustic Positioning

The cavitation noise of ducted transverse thrusters threatens to interfere with the operation of acoustic positioning or navigation systems as employed on ocean drilling ships, mining ships, and other work or scientific vessels so equipped. The design of an acoustically and hydrodynamically sophisticated transverse thruster is described in terms of its gross parameters and reasons for their selection. The design of the CRP propeller blades, which are of highly unorthodox form, is discussed in detail along with its conceptual basis. Model tests show that a large improvement in cavitation performance has been achieved while also maintaining efficiency. Measurements of the acoustic baffle effectiveness of the thruster duct, and engineering means to realize it, are described and applied to estimation of the interference noise levels expected to be sensed through the vessel's positioning system hydrophones.

scholarly journals Consistency of the Empirical Distributions of Navigation Positioning System Errors with Theoretical Distributions—Comparative Analysis of the DGPS and EGNOS Systems in the Years 2006 and 2014

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 31
Author(s):  
Mariusz Specht
Keyword(s):  
Normal Distribution ◽  
Root Mean Square ◽  
Statistical Tests ◽  
Position Error ◽  
Positioning System ◽  
Navigation Systems ◽  
Mean Square ◽  
Positioning Systems ◽  
Position Errors ◽  
System Errors

Positioning systems are used to determine position coordinates in navigation (air, land and marine). The accuracy of an object’s position is described by the position error and a statistical analysis can determine its measures, which usually include: Root Mean Square (RMS), twice the Distance Root Mean Square (2DRMS), Circular Error Probable (CEP) and Spherical Probable Error (SEP). It is commonly assumed in navigation that position errors are random and that their distribution are consistent with the normal distribution. This assumption is based on the popularity of the Gauss distribution in science, the simplicity of calculating RMS values for 68% and 95% probabilities, as well as the intuitive perception of randomness in the statistics which this distribution reflects. It should be noted, however, that the necessary conditions for a random variable to be normally distributed include the independence of measurements and identical conditions of their realisation, which is not the case in the iterative method of determining successive positions, the filtration of coordinates or the dependence of the position error on meteorological conditions. In the preface to this publication, examples are provided which indicate that position errors in some navigation systems may not be consistent with the normal distribution. The subsequent section describes basic statistical tests for assessing the fit between the empirical and theoretical distributions (Anderson-Darling, chi-square and Kolmogorov-Smirnov). Next, statistical tests of the position error distributions of very long Differential Global Positioning System (DGPS) and European Geostationary Navigation Overlay Service (EGNOS) campaigns from different years (2006 and 2014) were performed with the number of measurements per session being 900’000 fixes. In addition, the paper discusses selected statistical distributions that fit the empirical measurement results better than the normal distribution. Research has shown that normal distribution is not the optimal statistical distribution to describe position errors of navigation systems. The distributions that describe navigation positioning system errors more accurately include: beta, gamma, logistic and lognormal distributions.

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