A MFKF Based SINS/DVL/USBL Integrated Navigation Algorithm for Unmanned Underwater Vehicles in Polar Regions

Zhao, Lin; Kang, Yingyao; Cheng, Jianhua; Fan, Ruiheng

doi:10.23919/chicc.2019.8865737

Cited by 9 publications

(2 citation statements)

References 8 publications

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“…With the improvement of the accuracy of laser gyro, fiber-optic gyro, and micro-electromechanical system (MEMS) inertial guidance technology, as well as the decrease in the cost and volume, inertial guidance has been employed in a large number of applications for the solution of position and navigation under multi-sensors. For example, inertial guidance is usually combined with a global navigation satellite system (GNSS) for integrated navigation [ 26 , 27 , 28 ], with a Doppler velocity log (DVL) for underwater navigation [ 29 ], and with a radar or camera for simultaneous localization and mapping (SLAM) algorithms [ 30 ].…”

Section: Introductionmentioning

confidence: 99%

An Autocollimator Axial Measurement Method Based on the Strapdown Inertial Navigation System

Ma,

Li,

Liu

et al. 2024

Sensors

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Autocollimators are widely used optical axis-measuring tools, but their measurement errors increase significantly when measuring under non-leveled conditions and they have a limited measurement range due to the limitations of the measurement principle. To realize axis measurement under non-leveled conditions, this paper proposes an autocollimator axis measurement method based on the strapdown inertial navigation system (SINS). First, the measurement model of the system was established. This model applies the SINS to measure the change in attitude of the autocollimator. The autocollimator was then applied to measure the angular relationship between the measured axis and its own axis, based on which the angular relationship of the axis was measured via computation through signal processing and data fusion in a multi-sensor system. After analyzing the measurement errors of the system model, the Monte Carlo method was applied to carry out a simulation analysis. This showed that the majority of the measurement errors were within ±0.002° and the overall measurement accuracy was within ±0.006°. Tests using equipment with the same parameters as those used in the simulation analysis showed that the majority of the measurement errors were within ±0.004° and the overall error was within ±0.006°, which is consistent with the simulation results. This analysis proves that this method solves the problem of the autocollimator being unable to measure the axis under non-leveled conditions and meets the needs of axis measurement with the application of autocollimators under a moving base.

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Section: Introductionmentioning

confidence: 99%

An Autocollimator Axial Measurement Method Based on the Strapdown Inertial Navigation System

Ma,

Li,

Liu

et al. 2024

Sensors

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show abstract

“…However, the time integral operation in the navigation calculation process makes the errors of the inertial measurement components accumulate continuously, and the navigation performance of the system gradually decreases. Similarly, any single sensor has limitations of its working conditionality, so the task of measuring the navigation information of the underwater vehicle needs to be completed by the combination of multiple navigation devices [5,6]. The technology of integrated processing of two or more navigation sensor measurements is integrated positioning and navigation technology, which can make the navigation results more reliable.…”

Section: Introductionmentioning

confidence: 99%

Research on Error Correction Technology in Underwater SINS/DVL Integrated Positioning and Navigation

Zhu

et al. 2023

Sensors

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Underwater vehicles are key carriers for underwater inspection and operation tasks, and the successful implementation of these tasks depends on the positioning and navigation equipment with corresponding accuracy. In practice, multiple positioning and navigation devices are often combined to integrate the advantages of each equipment. Currently, the most common method for integrated navigation is combination of the Strapdown Inertial Navigation System (SINS) and Doppler Velocity Log (DVL). Various errors will occur when SINS and DVL are combined together, such as installation declination. In addition, DVL itself also has errors in the measurement of speed. These errors will affect the final accuracy of the combined positioning and navigation system. Therefore, error correction technology has great significance for underwater inspection and operation tasks. This paper takes the SINS/DVL integrated positioning and navigation system as the research object and deeply studies the DVL error correction technology in the integrated system.

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Real-time Underwater 3D Reconstruction Method Based on Stereo Camera

Hou

2022

2022 IEEE International Conference on Mechatronics and Automation (ICMA)

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A MFKF Based SINS/DVL/USBL Integrated Navigation Algorithm for Unmanned Underwater Vehicles in Polar Regions

Cited by 9 publications

References 8 publications

An Autocollimator Axial Measurement Method Based on the Strapdown Inertial Navigation System

An Autocollimator Axial Measurement Method Based on the Strapdown Inertial Navigation System

Research on Error Correction Technology in Underwater SINS/DVL Integrated Positioning and Navigation

Real-time Underwater 3D Reconstruction Method Based on Stereo Camera

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