ansfl/MissBeamNet
Learning Missing Doppler Velocity Log Beam Measurements
This helps autonomous underwater vehicle (AUV) operators and navigation engineers maintain accurate subsea navigation even when critical sensor data is incomplete. It takes in partial Doppler Velocity Log (DVL) beam measurements and uses them to predict the missing beam data. The output is a more complete set of DVL measurements, allowing the AUV's navigation system to continue estimating its velocity accurately.
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Use this if your autonomous underwater vehicles frequently encounter degraded DVL performance due to missing acoustic beam reflections, leading to compromised navigation accuracy.
Not ideal if your AUV navigation system relies solely on perfect DVL data or if you have alternative, robust methods for velocity estimation during DVL outages.
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Language
Python
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Last pushed
Mar 05, 2024
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