A novel filtering model for DVL aided inertial navigation system based on observability degree analysis

Yu, Huapeng; Geng, Yanli; Zhu, Hai; Jiang, Nuan; Chen, Jianhua

doi:10.1109/cgncc.2016.7828765

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…The observability issue was also reported in underwater and aerial navigations [27,28]. Due to the water resistance, maneuvers are hard to be obtained for autonomous underwater vehicles (AUV), which also leads to the poor observability of azimuth error and its rate gyro bias [27]. For the helicopter unmanned aerial vehicle (UAV), the GPS-aided inertial navigation system (INS) does not provide the observability of the azimuth during hover [28].…”

Section: Introductionmentioning

confidence: 91%

“…Similar conclusions are also indicated in [26], which shows that the azimuth and its rate gyro bias are unobservable in straight motion and with constant acceleration for land vehicle applications. The observability issue was also reported in underwater and aerial navigations [27,28]. Due to the water resistance, maneuvers are hard to be obtained for autonomous underwater vehicles (AUV), which also leads to the poor observability of azimuth error and its rate gyro bias [27].…”

Section: Introductionmentioning

confidence: 99%

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Improving Observability of an Inertial System by Rotary Motions of an IMU

Sun

Gao

2017

Sensors

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It has been identified that the inertial system is not a completely observable system in the absence of maneuvers. Although the velocity errors and the accelerometer bias in the vertical direction can be solely observable, other error states, including the attitude errors, the accelerometer biases in the east and north directions, and the gyro biases, are just jointly observable states with velocity measurements, which degrades the estimation accuracy of these error states. This paper proposes an innovative method to improve the system observability for a Micro-Electro-Mechanical-System (MEMS)-based Inertial Navigation System (INS) in the absence of maneuvers by rotary motions of the Inertial Measurement Unit (IMU). Three IMU rotation schemes, namely IMU continuous rotation about the X, Y and Z axes are employed. The observability is analyzed for the rotating system with a control-theoretic approach, and tests are also conducted based on a turntable to verify the improvements on the system observability by IMU rotations. Both theoretical analysis and the results indicate that the system observability is improved by proposed IMU rotations, the roll and pitch errors, the accelerometer biases in the east and north directions, the gyro biases become observable states in the absence of vehicle maneuvers. Although the azimuth error is still unobservable, the enhanced estimability of the gyro bias in the vertical direction can effectively mitigate the azimuth error accumulation.

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Section: Introductionmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Improving Observability of an Inertial System by Rotary Motions of an IMU

Sun

Gao

2017

Sensors

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“…At present, most underwater navigation systems are inertial navigation systems (INS). As the error of INS inevitably accumulates over time [1], many auxiliary measures need to be adopted, including Global Positioning System-(GPS-) aided methods [2,3], acoustic navigation methods [4,5], and Doppler velocity log-(DVL-) aided methods [6,7]. However, the limitation of these techniques is that the navigation system must rely on either electromagnetic wave signal (e.g., GPS signal), artificial beacons (e.g., long baseline), complex mathematical models (e.g., flow prediction model), or the accessibility of the sea bottom (e.g., DVL bottom tracking).…”

Section: Introductionmentioning

confidence: 99%

Terrain Matching Localization for Underwater Vehicle Based on Gradient Fitting

et al. 2018

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Terrain matching positioning is a promising method to overcome the problem that the inertial navigation error of the underwater vehicle accumulates over time. In the conventional terrain matching method, all measurement points are commonly used for matching and positioning. However, this method fails to be taken into a balanced consideration on both the computation complexity and the positioning accuracy. To reduce the computation and ensure the accuracy at the same time, an improved terrain matching method based on the gradient fitting is proposed in this paper. In the method, the gradient distributions of multiple terrain regions are firstly analyzed. Then, normal distribution is used to fit them, and according to the distribution, points with larger gradient values are selected as matching points. Finally, minimum absolute difference matching is chosen to match for positioning. Simulation results using multibeam sonar show that the improved terrain matching localization method not only reduces the computational complexity but also improves the accuracy of positioning.

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Analysis and Application of Geometric Dilution of Precision Based on Altitude-Assisted INS/SAR Integrated Navigation

Han

2021

IEEE Trans. Instrum. Meas.

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A novel filtering model for DVL aided inertial navigation system based on observability degree analysis

Cited by 3 publications

References 8 publications

Improving Observability of an Inertial System by Rotary Motions of an IMU

Improving Observability of an Inertial System by Rotary Motions of an IMU

Terrain Matching Localization for Underwater Vehicle Based on Gradient Fitting

Analysis and Application of Geometric Dilution of Precision Based on Altitude-Assisted INS/SAR Integrated Navigation

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