System reset of transversal strapdown INS for ship in polar region

Li, Qian; Ben, Yueyang; Yu, Fashan; Sun, Feng

doi:10.1016/j.measurement.2014.10.020

Cited by 30 publications

(27 citation statements)

References 6 publications

(16 reference statements)

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“…The mechanism of transverse navigation under the spherical Earth model is presented in Li et al (2015). Its corresponding damping technology and system reset process have been studied.…”

mentioning

confidence: 99%

Transverse Navigation under the Ellipsoidal Earth Model and its Performance in both Polar and Non-polar areas

Yao

et al. 2015

J. Navigation

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The transverse navigation system has been designed and developed to solve the challenges of navigation in polar regions. However, considerable theoretical errors are introduced into the system when the spherical Earth model is adopted. To tackle this problem, a transverse navigation mechanism under the ellipsoidal Earth model has been proposed in this research and the application regions of the proposed algorithm are specified and evaluated through error analysis. The analysis shows the presented transverse navigation system works in both polar and part of the non-polar regions. Field tests were conducted to evaluate the navigation performance in Nanjing, a non-polar region. A novel experimental method, where the field test data in mid-latitude areas was used to simulate the real Inertial Measurement Unit (IMU) data and the reference information in polar regions, was adopted to investigate the performance of the proposed algorithm in polar areas. The results show: that in the mid-latitude areas, the presented transverse navigation system achieves the same accuracy as the traditional inertial navigation system and that in polar regions, the proposed transverse mechanism outperforms the traditional method with a much lower error in longitude and yaw.

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“…The mechanism of transverse navigation under the spherical Earth model is presented in Li et al (2015). Its corresponding damping technology and system reset process have been studied.…”

mentioning

confidence: 99%

Transverse Navigation under the Ellipsoidal Earth Model and its Performance in both Polar and Non-polar areas

Yao

et al. 2015

J. Navigation

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show abstract

“…It is called conventional fine alignment. The initial alignment algorithm based on transversal navigation algorithm [20] is also chosen as the comparison model. It is called transversal coarse alignment algorithm and transversal fine alignment algorithm.…”

Section: Simulation and Experiments Resultsmentioning

confidence: 99%

A Polar Initial Alignment Algorithm for Unmanned Underwater Vehicles

Yan

Wang

et al. 2017

Sensors

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Due to its highly autonomy, the strapdown inertial navigation system (SINS) is widely used in unmanned underwater vehicles (UUV) navigation. Initial alignment is crucial because the initial alignment results will be used as the initial SINS value, which might affect the subsequent SINS results. Due to the rapid convergence of Earth meridians, there is a calculation overflow in conventional initial alignment algorithms, making conventional initial algorithms are invalid for polar UUV navigation. To overcome these problems, a polar initial alignment algorithm for UUV is proposed in this paper, which consists of coarse and fine alignment algorithms. Based on the principle of the conical slow drift of gravity, the coarse alignment algorithm is derived under the grid frame. By choosing the velocity and attitude as the measurement, the fine alignment with the Kalman filter (KF) is derived under the grid frame. Simulation and experiment are realized among polar, conventional and transversal initial alignment algorithms for polar UUV navigation. Results demonstrate that the proposed polar initial alignment algorithm can complete the initial alignment of UUV in the polar region rapidly and accurately.

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“…The typical dynamic model of the SINS shown in [ 24 ] is defined as Model 2. The dynamic model of the SINS shown in [ 13 ] is defined as Model 3. Model 1 and Model 3 are designed for navigation in the polar region, and Model 2 is designed for navigation in non-polar regions.…”

Section: Filter Models Of the Uuv In Polar Grid Navigationmentioning

confidence: 99%

“…Due to the rapid convergence of Earth meridians, small measurement errors would lead to significant calculation errors. To solve these problems, a transversal SINS algorithm is proposed to replace the traditional SINS algorithm in the polar region [ 13 ]. Although a system reset is used to restrain the error drifts, there are principle errors in the transversal SINS algorithm.…”

Section: Introductionmentioning

confidence: 99%

Polar Grid Navigation Algorithm for Unmanned Underwater Vehicles

Yan

Wang

Zhang

et al. 2017

Sensors

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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.

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System reset of transversal strapdown INS for ship in polar region

Cited by 30 publications

References 6 publications

Transverse Navigation under the Ellipsoidal Earth Model and its Performance in both Polar and Non-polar areas

Transverse Navigation under the Ellipsoidal Earth Model and its Performance in both Polar and Non-polar areas

A Polar Initial Alignment Algorithm for Unmanned Underwater Vehicles

Polar Grid Navigation Algorithm for Unmanned Underwater Vehicles

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