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

Abstract

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.

Localisation of Unmanned Underwater Vehicles (UUVs) in Complex and Confined Environments: A Review

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GSCV-XGBoost based information reconstruction and fusion method for SINS/DVL integrated navigation system

“…Liu et al (2017Liu et al ( , 2018 proposed the inertial navigation system (INS)/DVL/pressure sensor (PS) tightly coupled approach for the first time, to overcome the situation of unavailable beam measurements. Yoo et al (2020) further researched an INS/DVL/RPM integrated navigation system, to improve the performance of the traditional tightly coupled approach, where the revolutions per minute information (RPM) proposed can estimate the data from the faulty DVL transducer. With the broad variety of nonlinear model building applications, many algorithms have been validated and aided in different integrated navigation systems.…”

Modified Sage‐Husa Adaptive Kalman Filter‐Based SINS/DVL Integrated Navigation System for AUV

“…However, the navigation error of SINS is accumulated over time, which results in low navigation accuracy. In view of this problem, the Doppler velocimeter (DVL) is combined with SINS in [4][5][6][7] to construct the SINS/DVL integrated navigation system, where the navigation error of SINS is corrected by the DVL. To provide the accurate initial attitude angles to the SINS/DVL integrated navigation sys-tem, the initial attitude alignment algorithms for SINS/DVL are studied.…”