ArticlePloS one2026
GNSS/SINS/DVL integrated navigation algorithm based on adaptive differential Kalman filtering.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Research on Navigation Method for Subsea Drilling Robot Based on Inertial Navigation and Odometry.Sensors (Basel, Switzerland) · 2026Article
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5 authors.
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Abstract
The global navigation satellite system/strapdown inertial navigation system/doppler velocity logger (GNSS/SINS/DVL) integrated navigation system leverages the complementary advantages of its three subsystems to provide essential navigation information-such as attitude, velocity, and position-for carriers operating in marine environments. However, unmanned underwater vehicle (UUV) faces challenges like observation anomalies and dynamic model inaccuracies during dynamic maritime navigation and positioning. These issues make it difficult for the standard Kalman filter (KF) to cope with the complexities of the ocean environment, thereby reducing the accuracy of navigation parameter estimates. To address this, this study introduces an adaptive differential Kalman filtering (ADKF) method for processing integrated navigation data. Experimental results indicate that, compared with the KF, the proposed algorithm significantly enhances the accuracy and stability of parameter estimation, making it well-suited for post-processing integrated navigation data in complex marine settings.
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