A Hybrid Adaptive Velocity Aided Navigation Filter with Application to
INS/DVL Fusion
- URL: http://arxiv.org/abs/2211.01329v1
- Date: Sat, 8 Oct 2022 06:59:50 GMT
- Title: A Hybrid Adaptive Velocity Aided Navigation Filter with Application to
INS/DVL Fusion
- Authors: Barak Or and Itzik Klein
- Abstract summary: Inertial sensors are used in a nonlinear filter to estimate an AUV navigation solution.
A common practice is to assume that this matrix is fixed during the AUV operation.
We propose a learning-based adaptive velocity-aided navigation filter.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Autonomous underwater vehicles (AUV) are commonly used in many underwater
applications. Usually, inertial sensors and Doppler velocity log readings are
used in a nonlinear filter to estimate the AUV navigation solution. The process
noise covariance matrix is tuned according to the inertial sensors'
characteristics. This matrix greatly influences filter accuracy, robustness,
and performance. A common practice is to assume that this matrix is fixed
during the AUV operation. However, it varies over time as the amount of
uncertainty is unknown. Therefore, adaptive tuning of this matrix can lead to a
significant improvement in the filter performance. In this work, we propose a
learning-based adaptive velocity-aided navigation filter. To that end,
handcrafted features are generated and used to tune the momentary system noise
covariance matrix. Once the process noise covariance is learned, it is fed into
the model-based navigation filter. Simulation results show the benefits of our
approach compared to other adaptive approaches.
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