ansfl/MEMS-IMU-Denoising
Data-Driven Denoising of Accelerometer Signals
This project helps navigation system developers or robotics engineers improve the accuracy of low-cost inertial sensors like accelerometers. It takes raw accelerometer signals, often noisy from consumer-grade devices, and outputs significantly cleaner, more reliable data. This denoised data can then lead to more precise calculations for positioning, movement tracking, and system alignment, especially when GPS or other external signals are unavailable.
127 stars. No commits in the last 6 months.
Use this if you are working with consumer-grade inertial measurement units (IMUs) and need to enhance the accuracy of their accelerometer readings for navigation or attitude estimation tasks.
Not ideal if your primary concern is denoising gyroscope measurements or if you are using high-end, costly IMUs where sensor noise is already minimal.
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127
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23
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Last pushed
Jul 02, 2023
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