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Copy file name to clipboardExpand all lines: examples/imu_noise/README.md
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@@ -12,22 +12,48 @@ To evaluate noise, first build and run.
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mkdir build
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cd build
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cmake ..
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```
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### Ubuntu Or MacOS
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```bash
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make
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```
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This will generate the `sensor_noise` executable under `build`.
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### Windows
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```bash
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cmake --build . --config Release
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```
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This will generate the `sensor_noise.exe` executable under `build\Release`.
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```
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# Ubuntu or MacOS
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./sensor_noise
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# Windows
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.\Release\sensor_noise.exe
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```
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This will generate two series of samples, one for accelerometer and another for gyroscope.
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To use the analysis script, first install Allan Tools:
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```
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pip install --user allantools
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pip install --user allantools scipy
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```
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Then execute the script:
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```
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# Ubuntu o MacOS
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../plot_samples.py
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# Windows
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python.exe ..\plot_samples.py
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```
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This will produce two graphs: the Allan Deviation plots for both the simulated accelerometer and gyroscope. The values on these graphs should correspond closely to the inputs:
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* sigma_N: Accelerometer Noise Density
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* sigma_K: Accelerometer Random Walk
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While this technique is used here to validate the operation of the algorithm, it could also be used
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to estimate the noise parameters for a real IMU.
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## References:
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* Python Allan Tools: https://github.com/aewallin/allantools
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