A Novel Grid SINS/DVL Integrated Navigation Algorithm for Marine Application

Kang, Yingyao; Zhao, Lin; Cheng, Jianhua; Wu, Mouyan; Fan, Xiaoliang

doi:10.3390/s18020364

Cited by 29 publications

(21 citation statements)

References 24 publications

(27 reference statements)

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“…Both methods are designed for noise suppression in non-stationary vibration signals. Kang et al [ 36 ] proposed an adaptive robust Kalman filter (ARKF)-based hybrid-correction grid strapdown inertial navigation system (SINS)/doppler velocity log (DVL) integrated navigation algorithm to improve the navigation accuracy. Thus, ARKF method is also applied for effect comparison.…”

Section: Simulation Signal Analysismentioning

confidence: 99%

Improved Morphological Filter Based on Variational Mode Decomposition for MEMS Gyroscope De-Noising

Shen

Cao

et al. 2018

Micromachines

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An adaptive multi-scale method based on the combination generalized morphological filter (CGMF) is presented for de-noising of the output signal from a MEMS gyroscope. A variational mode decomposition is employed to decompose the original signal into multi-scale modes. After choosing a length selection for the structure element (SE), the adaptive multi-scale CGMF method reduces the noise corresponding to the different modes, after which a reconstruction of the de-noised signal is obtained. From an analysis of the effect of de-noising, the main advantages of the present method are that it: (i) effectively overcomes deficiencies arising from data deviation compared with conventional morphological filters (MFs); (ii) effectively targets the different components of noise and provides efficacy in de-noising, not only primarily eliminating noise but also smoothing the waveform; and (iii) solves the problem of SE-length selection for a MF and produces feasible formulae of indicators such as the power spectral entropy and root mean square error for mode evaluations. Compared with the other current signal processing methods, the method proposed owns a simpler construction with a reasonable complexity, and it can offer better noise suppression effect. Experiments demonstrate the applicability and feasibility of the de-noising algorithm.

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Section: Simulation Signal Analysismentioning

confidence: 99%

Improved Morphological Filter Based on Variational Mode Decomposition for MEMS Gyroscope De-Noising

Shen

Cao

et al. 2018

Micromachines

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“…A loosely coupled approach has a design advantage due to the simplicity of its measurements, but its accuracy in measuring body frame velocities is greatly impaired if any of the DVL transducer signals cannot be received. To overcome this drawback, various filter designs have also been proposed that use sensors other than DVL or apply a set of constraints [10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Performance Enhancement for Conventional Tightly Coupled INS/DVL Navigation System Using Regeneration of Partial DVL Measurements

Yoo¹,

Kim²,

Yoon

et al. 2020

Journal of Sensors

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Inertial navigation systems/Doppler velocity log (INS/DVL) integrated navigation systems are widely used in underwater environments where GPS is unavailable. An INS/DVL integrated navigation system is generally loosely coupled; however, this does not work if any of the DVL transducers do not work. If a system is tightly coupled, velocity error can be estimated with fair accuracy even if some of the transducers fail. However, despite the robustness of a tightly coupled system compared to a loosely coupled one, velocity error estimation accuracy of the former decreases as the number of faulty transducers increases. Therefore, this paper proposes an INS/DVL/revolutions per minute (RPM) integrated navigation filter designed to improve the performance of conventional tightly coupled integrated systems by estimating data from faulty transducers using RPM data. Two salient features of the proposed filter are (1) estimating RPM data accounting for error from the effect of tidal currents and (2) continuous estimation of error in RPM data by selectively converting only the measurements of faulty transducers. The performance of the proposed filter was first verified using Monte Carlo numerical simulations with the analysis range set to 1 standard deviation (1σ, 68%) and then with real sea test measurement data.

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“…The Doppler velocity log (DVL) is a good acoustic-based device in marine applications, which can provide three-dimensional velocities to mitigate the errors of marine SINS [ 4 , 5 , 6 ]. Therefore, the integrated SINS and DVL navigation system is a common navigation method for underwater or surface navigation during long voyages [ 7 , 8 , 9 ]. The SINS system error model is nonlinear, and a nonlinear filtering algorithm is generally used for state estimation.…”

Section: Introductionmentioning

confidence: 99%

Square-Root Unscented Information Filter and Its Application in SINS/DVL Integrated Navigation

Guo

Tang

et al. 2018

Sensors

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To address the problem of low accuracy for the regular filter algorithm in SINS/DVL integrated navigation, a square-root unscented information filter (SR-UIF) is presented in this paper. The proposed method: (1) adopts the state probability approximation instead of the Taylor model linearization in EKF algorithm to improve the accuracy of filtering estimation; (2) selects the most suitable parameter form at each filtering stage to simply the calculation complexity; (3) transforms the square root to ensure the symmetry and positive definiteness of the covariance matrix or information matrix, and then to enhance the stability of the filter. The simulation results indicate that the estimation accuracy of SR-UIF is higher than that of EKF, and similar to UKF; meanwhile the computational complexity of SR-UIF is lower than that of UKF.

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A Novel Grid SINS/DVL Integrated Navigation Algorithm for Marine Application

Cited by 29 publications

References 24 publications

Improved Morphological Filter Based on Variational Mode Decomposition for MEMS Gyroscope De-Noising

Improved Morphological Filter Based on Variational Mode Decomposition for MEMS Gyroscope De-Noising

Performance Enhancement for Conventional Tightly Coupled INS/DVL Navigation System Using Regeneration of Partial DVL Measurements

Square-Root Unscented Information Filter and Its Application in SINS/DVL Integrated Navigation

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